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Artificial Societies of Intelligent Agents Fundación Arturo Rosenblueth Artificial Societies of Intelligent Agents Thesis for majoring in Computing Engineering presented by: Carlos Gershenson García advisor: Dr. José Negrete Martínez México, 2001 “The best way to understand man is by creating him” —José Negrete Martínez Acknowledgements A Javier Fernández Pacheco, por inducirme a la investigación; a Jaime Lagunez Otero, por volverme adicto a ella; a Pedro Pablo González Pérez, por suministrarme y proveerme investigación; y a José Negrete Martínez, por mostrarme cómo disfrutarla. A mis amigos y profesores Fernando Contreras, José Luis Navarro, Miguel Armas Alemán, Jorge Vasconcelos, Jacobo Hernández Villamizar, Roberto Murcio, Octavio Luna, Adrián Trejo, Alejandro Iris, Eduardo Fuentes, José Enrique Álvarez, Alejandro Domínguez, Cresenciano Grave y Víctor Rivas. Gracias por compartir y transmitir su conocimiento. A mis amigos y compañeros de generación: Arturo Frappé, Armando Franyuti, Mauricio Ocampo, Octavio Rosas, Abraham Sánchez y Carlos Vázquez. Gracias por estos años de compartir conocimiento, aprendizaje, risas y dominó. A mis compañeros de la Fundación Arturo Rosenblueth de generaciones anteriores y posteriores. A la Fundación Arturo Rosenblueth, al Instituto de Química de la UNAM y a la Facultad de Filosofía y Letras de la UNAM, por darme la oportunidad de desarrollarme en sus aulas y pasillos. A la Fundación Telmex, por el apoyo motivacional y económico recibido a través de su beca. To Marvin Minsky, Pattie Maes, Andy Clark, Lotfi Zadeh, Raul Rojas, Jean-Arcady Meyer, Yaneer Bar-Yam, Jack Cohen, Amir Handzel, Push Singh, Jelle Zuidema, Raimo Tuomela, Santiago Zambrano, and Carlos Calderón, for the advices, comments, attention and inspiration they have given me. A mi familia, que siempre me ha motivado y apoyado. ="*b, HZ >, H@:\8@ *".T\ <>, ="*,0*J, >@ ,V. <>, *".T\ :`$@&\ 4 &,DJ. Contents Abstract .................................................................... vii Introduction ................................................................. 1 0.1. Behaviour and the Evolution of Cognition ............................... 2 0.2. Objects vs. Concepts ................................................. 5 0.3. Motivations ........................................................ 6 0.4. Structure ........................................................... 6 1. Behaviour-Based Systems .................................................... 8 1.1. Background ........................................................ 9 1.1.1. What do we understand for intelligence? ....................... 12 1.1.2. Will machines be able to have the same, or more intelligence than humans? ................................................. 13 1.2. What is a Behaviour-Based System? ................................... 14 1.3. Some Areas of Application of BBS .................................... 16 1.3.1. Robotics .................................................. 16 1.3.1.1. Why do we build intelligent robots? .................... 17 1.3.2. Software agents ............................................ 17 1.3.3. Artificial life ............................................... 18 1.3.4. Philosophy ................................................. 18 1.4. About BBS ........................................................ 19 2. Artificial Societies ......................................................... 20 2.1. Introduction to Complex Systems ..................................... 21 2.1.1. Behaviour-based systems as complex systems .................... 22 2.1.2. Social systems as complex systems ............................. 22 2.2. Artificial Societies? ................................................. 23 2.3. Previous Work on Artificial Societies .................................. 24 2.4. About Artificial Societies ............................................ 25 3. Behaviour-Based Intelligence ................................................ 26 3.1. Action Selection Mechanisms ........................................ 27 3.2. Behaviours Production Systems ....................................... 30 3.3. Blackboard Node Architecture ....................................... 31 3.4. Behavioural Columns Architecture: An Evolutionary Bottom-Up Approach ............................................................... 32 3.5. Modelling Reflex Behaviours ......................................... 34 iv 3.6. Modelling Reactive Behaviours ....................................... 35 3.7. Modelling Motivated Behaviours ..................................... 38 3.8. Modelling Learning ................................................. 44 3.8.1. Associative learning ......................................... 44 3.8.2.Dynamic adjustment of the motivation degree ................... 47 3.9. Properties of BeCA ................................................. 49 3.10. About the Behavioural Columns Architecture .......................... 51 4. Behaviour-Based Social Emergence ........................................... 54 4.1. An I&I Model for Social Action ...................................... 55 4.1.1. The learning of the imitation factors ........................... 57 4.2. Properties of I&I. .................................................. 59 4.3. About I&I ........................................................ 59 5. A Behaviours Virtual Laboratory ............................................. 61 5.1. Virtual Labs and Behaviours Virtual Labs .............................. 62 5.2. The Virtual Environment ............................................ 63 5.3. The Animats ...................................................... 64 5.3.1. The perceptual system ....................................... 64 5.3.2. The internal medium ........................................ 65 5.3.3. The motor system ........................................... 65 5.3.4. The behaviours repertoire .................................... 66 5.3.5. BeCA in the animats ........................................ 67 5.3.6. I&I in the animats .......................................... 68 5.4. The Interface ...................................................... 68 5.5. About the BVL .................................................... 70 6. Experiments .............................................................. 72 6.1. Intelligence in the BVL ............................................. 73 6.1.1. Modelling reflex behaviours .................................. 73 6.1.2. Modelling reactive behaviours ................................ 74 6.1.3. Modelling motivated behaviours .............................. 75 6.1.4. Primary and secondary classical conditionings ................... 75 6.1.5. Learning the motivation degree ............................... 77 6.1.6. Non persistence of a consummatory action in the presence of an aversive stimulus .................................................. 79 6.1.7. Degrees of motivation and reactiveness ......................... 80 6.2. Social Emergence in the BVL ........................................ 82 6.2.1. Imitation of behaviour ....................................... 82 6.2.2. Induction of behaviour ...................................... 83 6.2.3. Learning of the imitation parameters .......................... 84 6.2.4. Collective misbelief ......................................... 86 v 6.3. About the Experiments .............................................. 88 Conclusions ................................................................. 90 Understanding Societies ................................................ 92 Future Work: The Path to Cognition ...................................... 92 Future Culture: Artificial Cognition ...................................... 93 Beliefs and Misbeliefs .................................................. 93 Philosophical Implications .............................................. 94 Glossary .................................................................... 95 Index ...................................................................... 97 References ................................................................ 100 vi Abstract In this thesis we present our work, where we developed artificial societies of intelligent agents, in order to understand and simulate adaptive behaviour and social processes. We obtain this in three parallel ways: First, we present a behaviours production system capable of reproducing a high number of properties of adaptive behaviour and of exhibiting emergent lower cognition. Second, we introduce a simple model for social action, obtaining emergent complex social processes from simple interactions of imitation and induction of behaviours in agents. And third, we present our approximation to a behaviours virtual laboratory, integrating our behaviours production system and our social action model in animats. In our behaviours virtual laboratory, the user can perform a wide variety of experiments, allowing him or her to test the properties of our behaviours production system and our social action model, and also to understand adaptive and social behaviour. It can be accessed and downloaded through the Internet. Before presenting our proposals, we make an introduction to artificial intelligence and behaviour-based systems, and also we give notions of complex systems and artificial societies. In the last chapter of the thesis, we present experiments carried out in our behaviours virtual laboratory showing the main properties of our behaviours production system, of our social action model, and of our behaviours virtual laboratory itself. Finally,
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