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Search Plans University of Pennsylvania ScholarlyCommons IRCS Technical Reports Series Institute for Research in Cognitive Science October 1993 Search Plans Michael B. Moore University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/ircs_reports Moore, Michael B., "Search Plans" (1993). IRCS Technical Reports Series. 185. https://repository.upenn.edu/ircs_reports/185 University of Pennsylvania Institute for Research in Cognitive Science Technical Report No. IRCS-93-29. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/ircs_reports/185 For more information, please contact [email protected]. Search Plans Abstract People often do not know where things are and have to look for them. This thesis presents a formal model suitable for reasoning about how to find things and acting ot find them, which I will call sear“ ch behavior”. Since not knowing location of something can prevent an agent from reaching his desired goal, the ability to plan and conduct a search will be argued to increase the variety of situations in which an agent can succeed at his chosen task. Searching for things is a natural problem that arises when the blocks world assumptions (which have been the problem setting for most planning research) are modified by providing the agent only partial knowledge of his environment. Since the agent does not know the total world state, actions may appear to have nondeterministic effects. The significant aspects of the search problem which differ from previously studied planning problems are the acquisition of information and iteration of similar actions while exploring a search space. Since introduction of the situation calculus [MH69], various systems have been proposed for representing and reasoning about actions which involve knowledge acquisition and iteration, including Moore's work on the interaction between knowledge and action [Moo80]. Such systems can be used to infer properties of plans which have already been constructed, but do not themselves construct plans for complex actions. My concern with searching has to do with a sense that Moore's knowledge preconditions are overly restrictive. Morgenstern [Mor88] examined ways to weaken knowledge preconditions for an individual agent by relying on the knowledge and abilities of other agents. Lesperance's research [Les91] on indexical knowledge is another way of weakening the knowledge preconditions. I am trying to reduce the amount of information an agent must know (provided he can search a known search space). If you dial the right combination to a safe it will open, whether or not you knew in advance that it was the right combination. Search is a way to guarantee you will eventually dial the right combination. So what I am exploring is how to systematically construct a search that will use available knowledge to accomplish something the agent does not currently know enough to do directly. I claim it is possible for automated agents to engage in search behavior. Engaging in search behavior consists in recognizing the need for a search, constructing an effective plan, and then carrying out that plan. Expressing such a plan and reasoning about its effectiveness requires a representation language. I will select a representation language based on criteria derived from analyzing the search planning problem. Each of the three components of a system for engaging in search behavior will be designed and implemented to demonstrate that an automated agent can find things when he needs o.t Comments University of Pennsylvania Institute for Research in Cognitive Science Technical Report No. IRCS-93-29. This other is available at ScholarlyCommons: https://repository.upenn.edu/ircs_reports/185 The Institute For Research In Cognitive Science Search Plans (Dissertation Proposal) P by Michael B. Moore E University of Pennsylvania Philadelphia, PA 19104-6228 N October 1993 Site of the NSF Science and Technology Center for Research in Cognitive Science N University of Pennsylvania IRCS Report 93-29 Founded by Benjamin Franklin in 1740 Search Plans Michael B Mo ore July This researchwas supp orted by the following grants DARPA no NJ AROno DAAL C NSF no IRI and Ben Franklin no SC A DISSERTATION PROPOSAL in COMPUTER AND INFORMATION SCIENCE July Abstract People often do not know where things are and have to lo ok for them This thesis presents a formal mo del suitable for reasoning ab out how to nd things and acting to nd them which I will call search b ehavior Since not knowing lo cation of something can prevent an agent from reaching his desired goal the ability to plan and conduct a search will b e argued to increase the varietyofsituationsinwhichanagent can succeed at his chosen task Searching for things is a natural problem that arises when the blo cks world assumptions whichhave b een the problem setting for most planning research are mo died by providing the agent only partial knowledge of his environment Since the agent do es not know the total world state actions may appear to have nondeterministic eects The signicant asp ects of the search problem which dier from previously studied planning problems are the acquisition of information and iteration of similar actions while exploring a search space Since intro duction of the situation calculus MH various systems have b een prop osed for representing and reasoning ab out actions whichinvolveknowledge acquisition and iter ation including Mo ores work on the interaction b etween knowledge and action Mo o Such systems can b e used to infer prop erties of plans whichhave already b een constructed onstruct plans for complex actions My concern with searching has but do not themselves c to do with a sense that Mo ores knowledge preconditions are overly restrictive Morgen stern Mor examined ways to weaken knowledge preconditions for an individual agent by relying on the knowledge and abilities of other agents Lesp erances research Les on indexical knowledge is another wayofweakening the knowledge preconditions I am trying to reduce the amount of information an agentmust know provided he can searchaknown search space If you dial the rightcombination to a safe it will op en whether or not you knew in advance that it was the rightcombination Searchisaway to guarantee you will eventually dial the rightcombination So what I am exploring is how to systematically construct a search that will use available knowledge to accomplish something the agent do es not currently know enough to do directly I claim it is p ossible for automated agents to engage in search b ehavior Engaging in searchbehavior consists in recognizing the need for a search constructing an eective plan and then carrying out that plan Expressing such a plan and reasoning ab out its eectiveness requires a representation language I will select a representation language based on criteria derived from analyzing the search planning problem Each of the three comp onents of a system for engaging in searchbehavior will b e designed and implemented to demonstrate that an automated agent can nd things when he needs to ii Acknowledgement Iowe debts of gratitude to manyteachers and colleagues who have help ed shap e this research I esp ecially appreciate the help of my advisor Bonnie Lynn Webb er and fellow students who havecontributed to the AnimNL pro ject includin g Chris Geib Breck Baldwin Libby Levison Mike White and Barbara Di Eugenio This work has b eneted from discussion with other memb ers of Penns Computational Linguistics FeedbackForum CLiFF and our informal planning discussion group including Charlie Ortiz and Ron Rymon Finally the comments and advice of my dissertation committee Henry Kautz of ATT Norm Badler Dale Miller and Greg Provan all of Penn havebeeninvaluable in helping me clarify the direction in which this research will evolve iii Contents Abstract ii Acknowledgement iii Finding something The search planning problem Novel asp ects of the search planning problem A scenario calling for a searchplan Previous approaches to related problems Classical planning Informative actions Conditional planning Diagnosis Abstract search actions Planning for iteration Reactive systems or situated agents Monitoring plan execution A new approach to planning a search Application to the AnimNL pro ject Thesis claim Plan of prop osal Plan representation Criteria for a representation Indexicality Candidate formalisms Time and causation Attitudes Combined theories of change and mental state Meeting representation criteria Situation calculus examples Example searchplan A representation language for searchplans iv Prop erties of search plans Avoiding rep etition Ability Lo op termination Ability and search plans Ecient strategies Summary Correctness of a searchplan Plan construction Iteration schemata for search Interrupting a search Abandoning a search Recursive planner invocation Planning for a search Plan execution Description of execution of a searchplan Evaluating conditional expressions Selecting obstaclesite to search Executing a search plan
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