The AAAI-13 Conference Workshops

Reports

Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O’Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar

n The AAAI-13 Workshop Program, a Activity Context-Aware part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday System Architectures and Monday, July 14–15, 2013, at the The third workshop on activity context-aware system archi - Hyatt Regency Bellevue Hotel in Belle - vue, Washington, USA. The program in - tectures sought to explore architectures for intelligent con - cluded 12 workshops covering a wide text-aware systems delivering complex functionality, with di - range of topics in artificial intelligence, rect access to information, simplifying business processes and including Activity Context-Aware Sys - activities while providing domain-specific and task-specific tem Architectures (WS-13-05); Artifi - depth in interactive banking, insurance, wealth management, cial Intelligence and Robotics Methods finance, clinical, legal, telecom customer service, operations, in Computational Biology (WS-13-06); supply chain, connected living room, and personal assistants. Combining Constraint Solving with Such systems understand not just words, but intentions and Mining and Learning (WS-13-07); Computer Poker and Imperfect Infor - the context of the interaction. Such architectures are expect - mation (WS-13-08); Expanding the ed to dramatically improve the quality of proactive decision Boundaries of Health Informatics Using support provided by virtual agents by enabling them to seek Artificial Intelligence (WS-13-09); In - explanations, make predictions, generate and test hypothe - telligent Robotic Systems (WS-13-10); ses, and perform what-if analyses. The systems can provide Intelligent Techniques for Web Person - extreme personalization ( N = 1) by inferring user intent, mak - alization and Recommendation (WS- ing relevant suggestions, maintaining context, carrying out 13-11); Learning Rich Representations from Low-Level Sensors (WS-13-12); cost-benefit analysis from multiple perspectives, finding sim - Plan, Activity, and Intent Recognition ilar cases from organizational and personal episodic memory (WS-13-13); Space, Time, and Ambient before such cases are searched for, finding relevant documents Intelligence (WS-13-14); Trading Agent and answers, and finding issues resolved by experts in similar Design and Analysis (WS-13-15); and situations. The architectures are expected to enable meaning - Statistical Relational Artificial Intelli - fully relating, finding, and connecting people and informa - gence (WS-13-16). tion sources through discovery of causal, temporal, and spa - tial relations. This workshop sought to bring together researchers from the AI and human-computer interaction (HCI) communities to address key research challenges need - ed to create activity context-aware digital workspaces in the near future. Key highlights of the workshops included an introduction and review by Pankaj Mehra (Fusion-io) and strong motiva - tion for context-aware systems, followed by a keynote talk by

Benjamin Grosof (Coherent Knowl - alizations from episodic memory to great progress is being made on meth - edge Systems) on representing activity create semantic memory, using a com - ods to solve problems related to struc - context through semantic rule meth - bination of semantic memory and ture prediction, motion simulation, ods, deriving from experience in the episodic memory to guide users? What and design of biological macromole - Halo and Digital Aristotle work. The af - is the role of activity context working cules (proteins and nucleic acids). ternoon session saw a keynote talk by memory and its relationship to persist - The workshop brought together a di - Paul Lukowicz (DFKI) on architectures ent episodic and semantic memories? verse group of researchers from a vari - needed for large-scale collaborative so - Fast Scalable Hybrid Any-Time Reason - ety of subfields within AI and robotics, cial sensing. A special mention must be ing Systems for Context-Aware Assistance such as robot motion planning, evolu - made of Alex Memory’s (Science Appli - that combine numerical (and subsym - tionary computation, machine learn - cations International Corporation) ar - bolic) and knowledge-driven (symbol - ing, computational geometry, and chitecture for context-aware insider ic) approaches for reasoning, together kinematics. Three keynote speakers threat detection in security applica - with abductive reasoning, to create summarized seminal progress in bio - tions. Genoveva G. Heredero (Infosys) meaningful real-time guidance en - molecular modeling. A talk given by demonstrated multiple applications of gines. Mona Singh (Princeton University, De - a detailed architecture for intelligent Context Information Exchange and In - partment of Computer Science) high - speech-enabled context-aware systems. tegration: How can we integrate and ex - lighted research on understanding and The discussions in this workshop have ploit the growing amount of informa - modeling molecular interactions with a helped us to work with fellow re - tion available from devices, services, variety of techniques from machine searchers to define activity context- the environment, and the various learning and computational geometry. aware system architectures along the sources of general background knowl - A talk by Pierre Baldi (University of Cal - following themes, which will continue edge, in order to support activity con - ifornia Irvine, School of Information to be further explored in future work - text-recognition tasks? What common and Computer Sciences) outlined the shops at AAAI: ontologies or data vocabularies will be historical developments and the gener - Activity Modeling, Representation, useful? What communication tech - al principles behind deep architectures Recognition, Detection, Acquisition, Simu - niques and formalisms will be most ef - for learning, and showcased powerful lation and Prediction: Which (low-level) fective in specific domains? How can applications for prediction of biomole - the externalized cognitive state trans - human activities can be reliably cular structure. A talk by Yang Zhang fer be properly affected? What are the learned and detected? How indicative (University of Michigan, Department relevant use-case scenarios and collab - are those for human tasks and intent? of Computational Medicine and Bioin - oration environments? What are suit - Which granularities of activities could formatics) focused on prediction of ter - able software architectures, user inter - be chosen for creating an extensible hi - tiary structure in proteins, highlighting faces, developer tools, and bench- erarchy of human activity? What rep - state of the art research on threading- marking tools for activity-based com - resentation frameworks are most suit - based, template-free, and hybrid ap - puting? What kind of text, context, able for modeling activities and proaches and important lessons and and behavioral analytics are needed? context switching and for enabling open questions from successes and fail - Pankaj Mehra, Lokendra Shastri, and uniform context recall universally ures in CASP. Vikas Agrawal organized this work - (across devices, platforms, and tech - Workshop presentations addressed shop. This summary was written by nologies)? Do we need sublanguages Vikas Agrawal and Lokendra Shastri. five major themes. Papers on the com - for user-device-specific activity and The papers of the workshop were pub - putation of molecular motions high - context dialogue? What types of, and lished as AAAI Press Technical Report lighted robotics-inspired algorithms for how much, context information can be WS-13-05. modeling folding paths in proteins and captured and incorporated into activity detailed mapping of structural transi - models? How can we do so effectively tions in peptides (by Juan Cortés, Lydia and efficiently? Artificial Intelligence and Tapia, and Nancy Amato). A second Semantic Activity Reasoning: How to Robotics Methods in group of papers highlighted recent de - model and represent activities, objects, velopments on evolutionary search al - resources, actions, and their semantics Computational Biology gorithms and the particular promise of in their context during task perform - In the last two decades, many comput - multiobjective optimization for model - ance? How do we design activity/con - er scientists in artificial intelligence ing equilibrium structures of loops and text models to enable the searching of and robotics have made significant polypeptide chains in proteins (by repositories of previous activities that contributions to modeling biological Amarda Shehu and Yaohang Li). An - have behaviorally and semantically systems. Indeed, the fields of computa - other theme was assisted protein struc - similar components to current activity tional structural biology are now high - ture prediction with prior information requirements? What is the role of se - ly populated by researchers with di - on contacts (by Jianlin Cheng). Ad - mantic memory and episodic memory? verse backgrounds in search, planning, vanced mathematical concepts were in - What are the techniques needed to cre - learning, evolutionary computation, troduced to enhance protein structure ate, manage, and properly retrieve constraint programming, machine determination from data obtained by episodic memory and to derive gener - learning, data mining, and others, and X-ray crystallography by exploiting

WINTER 2013 109 Reports symmetry (by Gregory Chirikjian). A sity of Illinois at Urbana-Champaign, Computer Poker and global view of the relationship between USA) on amortized integer linear pro - sequence, structure, and function in gramming inference. The second talk Imperfect Information the protein universe was also provided was given by Ian Davidson (University Poker is the canonical game with im - (by Rachael Kolodny). of California, Davis, USA) on incorpo - perfect information and stochastic Amarda Shehu, Juan Cortés, and rating constraint satisfaction into hier - events. Agents playing the game must Jianlin Cheng cochaired this workshop. archy building, graph segmenting, and attempt to maximize their winnings This summary was written by Amarda clustering. Three of the peer-reviewed against an initially unknown adversary Shehu and Juan Cortés. The papers of papers addressed topics related to the in a large and complex environment, the workshop were published as AAAI use of machine learning to assist con - while trying to discover what hidden Press Technical Report WS-13-06. straint solving and applications, specif - information the opponent knows and ically, to improve search (Loth et al.), acting in order to hide their own pri - Combining Constraint predict algorithm runtime (Hutter et vate information. The task of creating al.), and facilitate interesting complex agents that can match or surpass pro - Solving with Mining and transportation problems (Aleksandrov fessional players in these human-scale Learning et al.). The remaining three papers con - domains is an exciting and active area sidered the use of constraints in various of research. The field of constraint solving has tra - machine-learning and data-mining Since 2006, the Annual Computer ditionally evolved quite independently contexts, specifically, using constraints Poker Competition (ACPC) has used from the fields of machine learning to assist the learning of Bayesian learn - the game of poker as a common test and data mining. In recent years, inter - ing (Yao et al.), feature construction bed for researchers investigating the ap - est has grown around the opportunities (Costa), and using constraints for pat - plication of artificial intelligence to sto - at the interfaces between these fields, tern mining (Guns et al.). Therefore, chastic imperfect information do - and the potential advantages of their the program was quite evenly split be - mains. Significant progress has been integration. Integration can work in tween papers from either a constraints made over the last eight years of the two ways; on the one hand, various or a machine-learning background. competition: computers have sur - types of constraint solvers can be in - The mix of attendees from the key passed human players at two-player cluded in machine-learning and data- scientific topic areas of the workshop mining algorithms, for example, to limit Texas Hold’em (the smallest game was a significant feature of the work - provide a uniform and effective way to played for high stakes by humans) and shop and was commented on through - characterize the desired solutions. On are now approaching optimal play, and out the event. There were many shared the other hand, machine learning can computer agents are continuing to im - interests among the participants, and it help address challenges in constraint prove in the more complex no-limit satisfaction and programming, both at was felt that this event, the second in and three-player variants. The Com - the level of search, by improving search the series, provided a basis for an inter - puter Poker and Imperfect Information or integrating intelligent metaheuris - esting and productive annual meeting Workshop brings together scientists tics, as well as at the level of modeling, for people with complementary inter - and competitors from the ACPC with for example, by learning constraints or ests and skills in these important re - researchers who study the broad class interactively supporting a decision search areas. A number of collabora - of imperfect information domains. maker. tions have been initiated as a result of A wide range of techniques from ar - While promising initial results have the workshop. tificial intelligence and machine learn - been achieved at these interfaces, many The workshop cochairs are grateful ing are used in poker and other imper - opportunities remain unexplored and to all the contributors to the workshop fect information domains, and the further research is needed in order to for helping make the event such a suc - workshop provides a venue for re - establish a systematic approach to this cess, and to the program committee searchers to present their research as integration. The main purpose of this members who reviewed every submis - oral and poster presentations. A con - workshop was to provide an open en - sion and selected the papers that were tinuing theme, this year and historical - vironment where researchers in ma - presented. We are also grateful to the ly, is the progress made in the field of chine learning, data mining, and con - Artificial Intelligence journal for finan - computational game theory, where straint solving could exchange ideas cial support. competitors attempt to approximate and discuss promising approaches, cru - Tias Guns (KU Leuven, Belgium), optimal Nash equilibrium strategies cial issues, open problems, and inter - Lars Kotthoff (University College Cork, that are guaranteed to do no worse esting formal- izations of new tasks. Ireland), Barry O’Sullivan (University than tie in two-player zero-sum games. The workshop program comprised College Cork, Ireland), and Andrea The ACPC has resulted in the develop - two invited talks and six peer-reviewed Passerini (University of Trento, Italy) ment of two algorithms that are more research papers. Both invited talks pre - cochaired this workshop. This report efficient in both time and memory sented interesting perspectives on the was written by Lars Kotthoff and Barry than previous approaches for solving use of constraint reasoning to support O’Sullivan. The papers of the workshop large imperfect information games. Pre - machine-learning tasks. The first invit - were published as AAAI Press Technical sentations in this area focused on state- ed talk was given by Dan Roth (Univer - Report WS-13-07. space approximation techniques, effi -

110 AI MAGAZINE Reports cient implementations of the state-of- that is coupled with an increased re - two sections. The first one grouped top - the-art counterfactual regret minimiza - liance on this data by health practi - ics related to classification and predic - tion algorithm, and techniques for tioners and patients. The main bound - tion problems, while the second dealt solving the game as a series of subprob - aries to fully leveraging the data are its with other complex problems. In the lems. sophisticated management, analysis, first section, papers focused on the con - Another major theme this year was and use of results. AI techniques are struction of classification and predic - the use of online and offline tech - very well suited to expand these tion models using machine-learning niques for modeling an agent’s adver - boundaries, thus facilitating advances techniques on different types of clini - saries and varying the agent’s actions to in the health informatics area that may cal data (images, typical alphanumeric better respond to them. This directly have a profound effect on patient out - information, and textual reports). The addresses the goal of the game of pok - comes. As such, the Health Informatics second section encapsulated work on er, which is to maximize the expected Using Artificial Intelligence workshop the analysis of other types of clinical winnings against an initially unknown is a forum to bring together health in - decision problems with a focus on group of adversaries, but historically formatics researchers and AI researchers identifying interactions and addressing has been a more challenging problem with the goal of improving patient out - them between concurrently applied than precomputing a robust nonadap - comes through innovation. CPGs, the strategies to preemptive as - tive agent. There was active debate on This year’s workshop received a large signment of caregivers to patients dur - defining the objective of the task, a number of submissions that were di - ing mass casualty incidents, and the presentation of a new online adapta - vided into two major tracks (applica - analysis of patient reviews of doctors. tion technique used in the ACPC, and tion and methodology related). In ad - To further foster interaction and help applications of machine-learning tech - dition to these tracks, one keynote and guide future research direction, the in - niques to building offline models of two invited speakers provided crucial vited speakers were joined by Wojtek agent behavior. insights into and directions for health Michalowski (University of Ottawa) to The results of the 2013 Annual Com - informatics research. The keynote pres - carry on a panel discussion. The pan - puter Poker Competition were also an - entation, Artificial Intelligence in Med - elists, with participation from the audi - nounced at the workshop and can be icine: It’s Back to the Future given by ence, discussed a number of topics in - found at www.computerpokercompeti - Mark Musen (Stanford University), cap - cluding physicians’ trust in AI’s ability tion.org. The ACPC is run over the two tured the theme of the workshop. In his to help them make decisions, AI re - months leading up to the workshop talk, Musen described the current op - searchers’ responsibility in physician with the goal of producing statistically portunities for innovation in health in - decisions aided by AI-based support significant results between every com - formatics thanks to advances in tech - systems, and the need to train physi - bination of competitors in every event. nology and changes in how medicine is cians in understanding complex deci - Finally, the workshop was used to delivered. He specifically advocated op - sion models. There was general agree - discuss the past and future of the An - portunities for resuscitating AI in ment that physicians should have nual Computer Poker Workshop. This health informatics and the need for some understanding of the technology began with an eight-year retrospective venues such as HIAI to learn from past helping them make decisions. Further, presentation by Michael Johanson, lessons and to exchange ideas to foster for the proposed AI solutions to be ac - who discussed the research progress future discoveries. cepted in practice we as researchers that the community has made over The application track began with an need to provide solutions to existing time. This set the stage for a discussion needs even if these problems are low of the future directions of the ACPC invited talk by Jay M. Tenenbaum (Cancer Commons) discussing oppor - level and simple to implement. and the workshop, including proposed Martin Michalowski, Wojtek rule changes, the introduction of new tunities to apply human and machine intelligence to organize and refine the Michalowski, Dympna O’Sullivan, and events, and challenges and opportuni - Szymon Wilk cochaired this workshop. ties facing the research area as a whole. knowledge about treating cancer. The papers in this track talked about the use This report was written by Martin Christopher Archibald and Michael Michalowski. The papers of the work - of ontologies to define, organize, inte - Johanson cochaired this workshop and shop were published as AAAI Press grate, and process information in pa - wrote this report. The papers of the Technical Report WS-13-09. workshop were published as AAAI Press tient health records and population Technical Report WS-13-08. health records. Additional insights into the use of semantic networks to de - Intelligent scribe and execute computational ex - Expanding the Boundaries periments helped round out the track. Robotic Systems of Health Informatics Us - The theory track began with an in - Robotics has shown dramatic progress ing Artificial Intelligence vited talk by Barry O’Sullivan (Univer - in recent years, driven in part by the sity College Cork) on the challenges development of standardized hardware The rapid development and expansion and opportunities for applying con - and open source software frameworks of health informatics results in a con - straint programming to gaining health that dramatically lower the effort re - stantly growing volume of available da - knowledge. Due to the diversity of pre - quired to obtain a working robot sys - ta with diversified structure and format sented topics, this track was split into tem. These advances represent an ex -

WINTER 2013 111 Reports citing opportunity for AI researchers, simple, for example, making the pres - Anand, and Bamshad Mobasher co- because they have brought robot tech - entation more pleasing, but can also be chaired this workshop. This report was nology to the point where there is a complex when the aim, for example, is written by Dietmar Jannach. The papers pressing need for integrating AI tech - to anticipate the needs of a user and of the workshop were published as AAAI niques into robot systems. The task of provide information in a customized Press Technical Report WS-13-11. designing complete, intelligent robotic form. Recommender systems represent systems presents us with the opportu - one special and prominent class of per - nity to develop fully fledged agents sonalized web applications, which fo - Learning Rich that interact with the real world, and cus on the user-dependent filtering and Representations from the challenge of coping with the com - selection of relevant information and Low-Level Sensors plexity and uncertainty that such in - aim to support online users in the deci - teraction entails, leading to an im - sion-making and buying process. The A human-level artificially intelligent mensely rich source of research recent developments in the area of rec - agent must be able to represent and directions that have the potential for ommender systems — in particular in reason about the world, at some level, significant real-world impact. Robotics the context of the social web — gener - in terms of high-level concepts such as also offers us an opportunity to inte - ate new demands, in particular with re - entities and relations. The problem of grate the disparate subfields of AI, and spect to interactivity, adaptivity, and acquiring these rich high-level repre - drive progress in each subfield through user-preference elicitation. These chal - sentations has long been an obstacle the grand challenge of intelligent ro - lenges, however, are also in the focus of for achieving human-level AI. A popu - botics. general web personalization research. lar approach to this problem is to hand - This workshop built on the success The workshop therefore aimed to craft these high-level representations, but this has had limited success. An al - of two prior events, Designing Intelli - bring together practitioners and re - ternate approach is for rich representa - gent Robots: Reintegrating AI, at the searchers from the partially overlap - tions to be learned autonomously from AAAI Spring Symposia at Stanford, and ping fields of web personalization and low-level sensor data. Potentially, the the AI Meets Robotics meetings in Öre - recommender systems to discuss cur - latter approach may yield more robust bro and Lyon. The workshop drew par - rent and emerging topics in their re - representations and should require less ticipants from all over the world, in - spective fields and to foster an ex - cluding five invited speakers and 20 reliance on human knowledge engi - change of ideas and experiences. contributed papers, and closed with a neering. The workshop was opened with an lively discussion on future directions. The goal of this workshop was to invited talk by Guy Shani from the In - Byron Boots, Nick Hawes, Todd Hes - provide an informal forum for dis - formation Systems Engineering depart - ter, George Konidaris, Tekin Merili, cussing sensor-learning approaches to ment at the Ben Gurion University, Is - Lorenzo Riano, Benjamin Rosman, and the problem of how a machine may ac - rael. In his talk, Shani reported on Peter Stone cochaired this workshop. quire a broad range of knowledge about recent results on user interaction as - This report was written by George the world. Approximately 25 partici - pects in recommender systems applica - Konidaris. The papers of the workshop pants attended this workshop to dis - tions and in particular on the role of were published as AAAI Press Technical cuss the 11 accepted papers and 4 in - relevance displays and how they affect Report WS-13-10. vited talks representing different the user acceptance of such systems. approaches to bridging the gap be - The technical papers presented in tween low-level sensors and rich high- Intelligent Techniques for different themed sessions were selected level representations. Papers included Web Personalization and in a peer-review process by an interna - approaches from areas such as develop - tional program committee and covered Recommendation mental psychology, neuroscience, deep a variety of topics related to web per - learning, robotics, machine vision, and The role of personalization of web- sonalization and recommendation. reinforcement learning. based systems and the automatic rec - The topics of the papers ranged from Although the approaches differed, ommendation of potential items of in - the automated generation of music some recurring themes emerged from terest to users is probably higher today playlists and revenue-maximizing the discussion. One theme was the im - than ever before: search engines per - movie recommendations, over ap - portance of learning hierarchical repre - sonalize more and more their results proaches for interactive search and sentations, whether these are feature for a particular user, social media sites configuration to social and contextual hierarchies in connectionist networks automatically highlight or filter activi - recommendation techniques. or hierarchies of macro-actions in rein - ty feeds and suggest friends to connect The discussions after the technical forcement learning. In general, hierar - to, and companies even announce mil - paper presentations were centered on chies were learned in a bottom-up lion dollar prizes for improvements in questions related to the use of contex - manner, with lower-level features mak - the area of e-commerce personaliza - tual information in the recommenda - ing it possible for systems to learn high - tion. Web personalization in general tion process as well as on problems of er-level representations. Another aims to tailor the web experience to a designing and conducting user studies theme was the importance of generali - particular user or set of users. The goals for evaluation purposes. ty and modality independence of of personalization can be comparably Dietmar Jannach, Sarabjot Singh learning algorithms. If a large amount

112 AI MAGAZINE Reports of knowledge is to be learned, then level AI was stressed, as well as the need tions at the workshop this year illus - learning algorithms that are tailored to for researchers from disparate areas to trated the interesting synergy between a specific modality (such as vision) compare notes on this common obsta - models for planning (taking action) won’t be as flexible as more general- cle to these areas. and plan recognition (interpretation) purpose learning mechanisms. Marc Pickett, Benjamin Kuipers, (Khan, Arif, and Boloni; Smith and The workshop also raised several Yann LeCun, and Clayton Morrison Lieberman; Vered and Kaminka). questions. One open question is cochaired this workshop. The report This year, we were delighted to have whether distinct algorithms are re - was written by Marc Pickett. The papers Prashant Doshi (University of Georgia) quired for learning different levels of of the workshop were published as and Jerry Hobbs (USC ISI) as our guest representation, or whether it is possible AAAI Press Technical Report WS-13-12. speakers; their invited talks were one of for a single algorithm to learn all these the highlights of the workshop. The levels. Jeff Hawkins described a system, new poster session provided additional modeled on the human cortex, that Plan, Activity, and opportunities for workshop partici - was essentially the same general-pur - Intent Recognition pants to have more in-depth technical discussions at the side of the posters. pose learning and inference algorithm Plan, activity, and intent recognition repeated many times. Alternatively, The workshop concluded with a tradi - (PAIR) all involve making inferences tional group dinner, which many of Benjamin Kuipers and Joseph Modayil about other actors from observations of both described systems that spanned the participants attended. their behavior, for example, their inter - Hung Bui, Gita Sukthankar, Christo - much of the bridge from raw sensors to action with the environment or with high-level representations, but that pher Geib, and David V. Pynadath each other. Techniques for plan, activi - cochaired this workshop. The report used different algorithms for different ty, and intent recognition play a crucial stages. Kuipers outlined a “40-year-vi - was written by Hung Bui, Gita Suk - role in a wide variety of applications in - thankar, and Christopher Geib. The pa - sion” on how the bridge could be com - cluding personal assistant technology, pletely spanned. pers of the workshop were published as security systems, gaming and simula - AAAI Press Technical Report WS-13-13. Another question is how a system tion, human-robot interaction, and au - can learn relations from sensor data tomated dialogue systems. For this rea - that isn’t explicitly relational. For ex - son, the problem has continued to Space, Time, and ample, how can the relation “above” be receive attention from researchers in a Ambient Intelligence learned given only the raw pixels of number of areas: human-computer in - many still images? This is related to the teraction, autonomous and multiagent The Space, Time, and Ambient Intelli - question of how causality might be systems, machine vision, and natural gence workshops focus on basic re - learned from sensor data. Amy Fire language understanding. search questions concerned with the demonstrated a system that was able to An important topic concerning the computational modeling of common - learn perceptual causality from videos. PAIR community is how to make effi - sense situational awareness for assistive Both George Konidaris and Jonathan cient and accurate inference about an technologies within the purview of am - Mugan made headway into the ques - agent’s hidden plans and intents from bient intelligence and smart environ - tion of how symbols might be learned the potentially noisy observation of the ments. Space, time, and ambient intel - from sensor data. Konidaris presented a agent’s external behavior. Following ligence research topics address systems system that creates symbols in a con - the tradition of PAIR, many technical concerned with observing, interpret - tinuous reinforcement learning do - presentations at the workshop contin - ing, and interacting in an environment main, while Mugan described a system ue to push the envelope in addressing populated by humans and artifacts; the that learns qualitative representations this key issue. Approaches presented emphasis is on formal methods for rep - from a continuous domain in a top- include constructing expressive proba - resenting and reasoning about spa - down manner. bilistic-logical representations of an tiotemporal-, event-, and action-driven Finally, both Yoshua Bengio and agent’s behavior (Song, Kautz, and phenomena that occur in the environ - Juergen Schmidhuber presented im - Luo), dealing with agents acting in ex - ment or domain of interest. pressive recent advances from the deep ploratory manner (Uzan, Dekel, and This workshop focused on the topic learning community. For example, Gal), strategies for parallelization (Geib of spatiotemporal aspects of human ac - Schmidhuber presented a system that and Swetenham), incremental abduc - tivity interpretation, welcoming re - learns to drive a simulated car given tion (Meadows, Langley, and Emery). search concerned with the interpreta - video data. An open question is how Also presented was empirical analysis tion of people interactions, real-time deep learning can be extended to learn on how well different techniques work commonsense situational awareness relational representations, such as in a number of different domains, in - involving aspects such as scene percep - those used in natural language. cluding activity recognition bench - tion and understanding, perceptual da - At the end of the workshop, partici - marks (Ross and Kalleher; Nazerfard ta analytics, and prediction and expla - pants engaged in a general discussion. and Cook) and mobile text prediction nation-driven high-level control of Although no definite conclusions were (Freedman et al.). Taking a more gener - autonomous systems. In addition to six reached, the importance of learning al perspective in the context of multia - paper presentations, the workshop fea - representations for achieving human- gent interaction, a cluster of presenta - tured two invited keynote speakers: An -

WINTER 2013 113 Reports thony Cohn (University of Leeds, UK) tion, and others. In addition to research ing reinforcement learning, prediction and Henry Kautz (University of interest, trading agents have potential of customer demand in energy market Rochester, USA). benefits in electronic commerce, sup - simulations using machine learning, as The technical program of the work - ply-chain management, and other busi - well as analysis of Power Trading Agent shop also included prototypical demon - ness interests. Since 2003 Trading Agent Competition trading agent key per - strations and initiatives on benchmark - Design and Analysis (TADA) workshops formance indicators. The workshop ing and promotion of open-access have been focused on all aspects of the concluded with a demonstration of the algorithms and systems from the view - design and evaluation of trading AdX game, a new version of a Trading point of cognitive vision, interaction, agents, including agent architectures, Agent Competition game in the domain and control. The two discussion ses - decision-making algorithms, theoretic of Internet ad auctions and a discussion sions at the workshop also focused on analysis of agents or market games, em - on emerging application areas of trad - benchmarking and tool development pirical studies of agent performance, ing agents. with an emphasis on commonsense ab - agent negotiation strategies, game-the - The Trading Agent Design and straction and reasoning (about human oretic studies, market architectures, and Analysis workshop traditionally coin - activities) encompassing aspects such as other related topics. cides with the final rounds of the Trad - common sense, space, and change. Additionally, a special characteristic ing Agent Competition and many of Some questions that were discussed in - of Trading Agent Design and Analysis the contestants participate in the work - cluded what is the status quo in open- workshops is a set of papers related to shop venue. The Trading Agent Com - source development and benchmarking Trading Agent Competition scenarios, petition finals are also used as a way to in high-level cognitive interpretation? covering analyses of strategies used in promote research on trading agents to a What kind of interfacing (for example, previous Trading Agent Competitions, broader audience and to generate inter - logic programming interface, APIs) and discussions about the effectiveness of est in new application areas for agent syntactic sugar would be needed to use different approaches, as well as technologies. For example, the Power commonsense methods for modeling, thoughts on applying the lessons Trading Agent Competition, a new reasoning, and learning about space, ac - learned through the Trading Agent Trading Agent Competition scenario fo - tions, events, change, and interaction? Competition to other domains. Trading cusing on smart grid markets, generat - How could reasoning plug in to large- Agent Design and Analysis has a long ed significant interest within the com - scale or hybrid activity recognition / in - and successful history being colocated munity and has attracted new terpretation projects? What kinds of at different artificial intelligence con - workshop participants with interests in general developmental, debugging, vi - ferences, including two previous work - energy applications. The inaugural edi - sualisation capabilities would be needed shops hosted by AAAI in 2007 and tion of Power Trading Agent Competi - to support a broad range of cognitive vi - 2008. tion finals as well as the Trading Agent sion projects? The international program commit - Competition Ad Auctions finals were A general consensus was that re - tee comprising 26 researchers from collocated with the TADA-13 work - search and development in the field academe and industry selected seven shop. The TacTex team from the Uni - needs to work on open availability and papers for presentation at the work - versity of Texas at Austin (USA) led by accessibility of data (for example, RGB shop. Papers presented at the workshop Daniel Urieli won the first Power Trad - and depth profile), and tool sets for spa - spanned from empirical analyses of real- ing Agent Competition, while the TAU tiotemporal abstraction, reasoning, world Internet-based trading agent sys - agent from Tel Aviv University (Israel), learning, and data visualisation. tems to initial explorations of trading led by Mariano Schain, performed best Mehul Bhatt, Hans W. Guesgen, and agent solutions in emerging application in the Trading Agent Competition Ad Diane J. Cook cochaired this workshop areas such as smart grid environments. Auctions. and wrote this report. The papers of the The workshop started with two papers The Trading Agent Competition workshop were published as AAAI Press dealing with auctions: auctioneer prof - board members provided guidance on Technical Report WS-13-14. itability in QuiBids penny auctions and organization matters, and Ioannis Vet - sikas (NCSR Demokritos, Greece) was price dependencies in simultaneous involved in organizational matters re - sealed-bid auctions were analyzed. The Trading Agent Design lated to the Trading Agent Competition. remainder of the presentations were re - Vedran Podobnik chaired this work - and Analysis lated to the Trading Agent Competition: shop and wrote this report. The papers Trading agents are a prominent area of there was a paper on detection of op - of the workshop were published as research in artificial intelligence and portunistic bids in the TAC Supply AAAI Press Technical Report WS-13-15. multiagent systems. The design and Chain Management scenario as well as a analysis of trading agents poses signifi - set of papers from a domain of the new cant challenges in decision making, Trading Agent Competition scenario fo - Statistical Relational and many different artificial intelli - cusing on energy markets. Power Trad - Artificial Intelligence gence techniques have been combined ing Agent Competition papers covered in the study of trading agents, includ - challenges such as electricity demand Much has been achieved in the field of ing planning, decision theory, game forecasting using Gaussian processes, AI, “the science and engineering of theory, machine learning, optimiza - smart charging for electric vehicles us - making intelligent machines” as John

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McCarthy defined it, yet much remains In addition, the workshop had three Dietmar Jannach is a chaired professor of to be done if we are to reach the goals invited speakers, Dan Suciu (University computer science at TU Dortmund, Ger - we all imagine. One of the key chal - of Washington), Prasad Tadepalli (Ore - many. lenges with moving ahead is closing the gon State University), and Toby Walsh Michael Johanson is a Ph.D. student at the gap between logical and statistical AI. (NICTA). The topics of these presenta - University of Alberta in Edmonton, Canada. Logical AI has mainly focused on com - tions explored the connections be - Kristian Kersting heads the statistical rela - tween statistical relational AI commu - plex representations, and statistical AI tional mining group at Fraunhofer IAIS and on uncertainty. Clearly, however, intel - nity and (1) probabilistic databases, (2) the University of Bonn, Germany. ligent machines must be able to handle constraint satisfication, and (3) rela - the complexity and uncertainty of the tional MDPs. Another interesting part George Konidaris is a postdoctoral associate real world. of the workshop was a lively poster ses - at MIT. Recent years have seen an explosion sion that encouraged the participants Lars Kotthoff is a postdoctoral research sci - of successes in combining probability to discuss the commonalities and need entist at the INSIGHT Centre for Data Ana - and (subsets of) first-order logic, pro - for differences among the various AI lytics, University College Cork. gramming languages, and databases in tasks that can be addressed by SR tech - Martin Michalowski is a principal research several subfields of AI such as reason - niques. The group reached a general scientist at Adventium Labs in Minneapolis, ing, learning, knowledge representa - consensus that statistical relational AI is MN. tion, planning, databases, natural lan - an exciting emerging area requiring Sriraam Natarajan is an assistant professor more investigation. The topic of effi - guage processing, robotics, vision, and at the School of Informatics and Computing others. cient and lifted inference found partic - at Indiana University, Bloomington, IN, Nowadays, we can learn probabilistic ular interest. USA. relational models automatically from Kristian Kersting, Vibhav Gogate, Sri - millions of interrelated objects. We can raam Natarajan, and David Poole Barry O’Sullivan is a full professor in the Department of Computer Science at Univer - generate optimal plans and learn to act cochaired this workshop and wrote this sity College Cork (Ireland) and director of optimally in uncertain environments report. The papers of the workshop the INSIGHT Centre for Data Analytics, Uni - involving millions of objects and rela - were published as AAAI Press Technical versity College Cork. tions among them. Exploiting shared Report WS-13-16. factors can speed up message-passing Marc Pickett is an NRC postdoctoral fellow Vikas Agrawal is a research staff member at at the Naval Research Laboratory in Wash - algorithms for relational inference but IBM Research-India. ington, DC. also for classical propositional inference such as solving SAT problems. We can Christopher Archibald is an assistant pro - Vedran Podobnik is an assistant professor at even perform lifted probabilistic infer - fessor in the Department of Computer Sci - the Telecommunication Department of the ence and Engineering at Mississippi State ence, avoiding explicit state enumera - Faculty of Electrical Engineering and Com - University. puting, University of Zagreb, Croatia. tion by manipulating first-order state representations directly. So far, howev - Mehul Bhatt is a researcher in the Cognitive David Poole is a professor at the Depart - er, the researchers combining logic and Systems, and Spatial Cognition Research ment of Computer Science, University of probability in each of these subfields Center at the University of Bremen, Ger - British Columbia, Vancouver, Canada. many. have been working mostly independ - Lokendra Shastri is the associate vice presi - ently. This workshop was designed for Hung Bui is a principal research scientist at dent, GM Research, and head of the Center attempts at synthesis, forming a com - the Laboratory for Natural Language Under - for Knowledge Driven Intelligent Systems at mon core of problems and ideas, cross- standing, Nuance, Sunnyvale, CA. Infosys, India. pollinating across subareas, and ulti - Diane J. Cook is a chaired professor in the Amarda Shehu is an assistant professor in mately starting to explore what might School of Electrical Engineering and Com - the Department of Computer Science at be called statistical relational AI: the puter Science at Washington State Universi - George Mason University. study and design of intelligent agents ty. Gita Sukthankar is a Charles N. McMillan that act in noisy worlds composed of Juan Cortés is a researcher with the LAAS- faculty fellow and an associate professor in objects and relations among the ob - CRNS Laboratory at the University of the Department of Electrical Engineering jects. Toulouse. and Computer Science at the University of The 21 papers and posters at the Central Florida. workshop covered a wide range of sta - Christopher Geib is an associate professor tistical relational AI topics such as lifted in the College of Information Science and inference, natural language processing, Technology, Drexel University. online rule learning, event recognition, Vibhav Gogate is an assistant professor at tractable relational representations, re - the Department of Computer Science, Uni - lational Markov decision processes versity of Texas at Dallas, USA. (MDPs), and learning statistical rela - Hans W. Guesgen is a professor of comput - tional learning (SRL) models, thus clear - er science in the School of Engineering and ly showing the promise of statistical re - Advanced Technology at Massey University, lational (SR) techniques for AI. New Zealand.

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