Intelligent Systems: Robots, Agents, and Humans

This course is a study of systems that exhibit intelligent attributes. We cover practical techniques for designing intelligent agents capable of planning, learning, and cooperation. There will be discussion of psychological/social ramifications of the use and creation of intelligent systems. Much of the course focuses on various challenge problems (e.g. the Trading Agent Competition and Robocup) that have been used to benchmark the performance of intelligent systems.

Prerequisites

• Instructor permission.

Objectives

• understand design issues facing the creators of intelligent systems
• understand research issues relating to the problem of creating human-like systems;
• learn practical techniques in planning, learning, three-tier architectures, and cooperation relevant to multi-agent and multi-robot systems;
• implement intelligent agents for a variety of domains;

Due Dates

• Final Exam (take-home), out on Mar 25th, due on Apr 1st
• Paper Presentations: Apr 1-17th
• Homework: Apr 11th
• Final Project Writeup (latex template, word template): Apr 24th
• Final Project Demo: Apr 23rd 1-4pm HEC 111

Outline

1. Introduction
   • Reading: Katia Sycara, Multiagent Systems, AI Magazine 19(2): Summer 1998, 79-92
2. Multiagent Systems
   • Reading: D. Nau, Current trends in automated planning, AI Magazine, Winter 2007
3. Introduction to Planning
   • Reading: Michael van Lent, Mark O. Riedl, Paul Carpenter, Ryan McAlinden, and Paul Brobst, Increasing Replayability with Deliberative and Reactive Planning. Proceedings of the 1st Conference on Artificial Intelligence and Interactive Digital Entertainment, Marina del Rey, California, 2005.
4. Planning in Computer Games
   • Reading: S. Lee-Urban, H. Munos-Avila, A. Parker, U. Kuter, and D. Nau, Transfer Learning of Hierarchical Task-Network Planning Methods in a Real-Time Strategy Game. Proceedings of ICAPS Workshop on Planning and Learning, 2007
5. Combining Planning and Learning
   • Reading: A. Greenwald and P. Stone, Autonomous Bidding Agents in the Trading Agent Competition IEEE Internet Computing, 5(2):52.60, March/April 2001.
6. Trading Agent Competition
   • Reading: A. Greenwald and J. Boyan Bidding Under Uncertainty: Theory and Experiments In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence (Jul 2004), pp. 209-216.
7. Bidding under Uncertainty
   • Reading: David Pardoe and Peter Stone. An Autonomous Agent for Supply Chain Management. In Gedas Adomavicius and Alok Gupta, editors, Handbooks in Information Systems Series: Business Computing, Elsevier, 2007
8. TAC: Supply Chain Management
   • Reading: Teacy, W. T. L., T. D. Huynh, R. K. Dash, N. R. Jennings, J. Patel, and M. Luck. The ART of IAM: The Winning Strategy for the 2006 Competition, The Workshop on Trust in Agent Societies at The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-2007), Honolulu, Hawaii, USA, May 15, pp. 102-111
9. Agent Reputation and Trust
   • Reading: Peter Stone, Manuela Veloso, and Patrick Riley. The CMUnited-98 Champion Simulator Team. In M. Asada and H.Kitano, editors, RoboCup-98: Robot Soccer World Cup II Lecture Notes in Artificial Intelligence, pp. 61.76, Springer Verlag 1999.
10. Robocup
    • Reading: Wang, J., Lewis, M., and Scerri, P. (2006). Cooperating robots for search and rescue, Proceedings of the AAMAS 1st International Workshop on Agent Technology for Disaster Management, 92-99.
11. Urban Rescue Robots
    • Reading: Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4:237--285, May 1996
12. Reinforcement Learning
    • Reading: Peter Stone and Manuela Veloso. Team-Partitioned, Opaque-Transition Reinforcement Learning. In Minoru Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer World Cup II, Lecture Notes in Artificial Intelligence, pp. 261.72, Springer Verlag, Berlin, 1999. Also in Proceedings of the Third International Conference on Autonomous Agents, 1999
13. Multi-Agent Reinforcement Learning
    • Matthew E. Taylor and Peter Stone. Cross-Domain Transfer for Reinforcement Learning. In Proceedings of the Twenty-Fourth International Conference on Machine Learning, June 2007.
14. Transfer Reinforcement Learning
    • Reading: M. Dias, M. Zinck, R. Zlot, and A. Stentz, Robust Multirobot Coordination in Dynamic Environments, In Proceedings of International Conference on Robotics and Automation, 2004
15. Multi-robot Coordination
    Reading: M. Koes, I. Nourbakhsh, and K. Sycara. Constraint Optimization Coordination Architecture for Search and Rescue Robotics, in Proceedings of ICRA 2006, Orlando, FL, May 2006, pp. 3977-3982.
16. Multi-agent Coordination (Team Planning)
    Reading: R. Nair, M. Tambe, and S. Marsella. Role allocation and re-allocation in multiagent teams: towards a practical analysis, in Proceedings of AAMAS-2003
17. No Class (Mar 11-13th)
18. Emulating Humans (Emotion)
    • Reading: J. Gratch and S. Marsella, Tears and Fears: Modeling emotions and emotional behaviors in synthetic agents, Proceedings of AAMAS-2001
19. Emulating Humans (Motion)
    • Reading: G. Sukthankar, M. Mandel, and K. Sycara, Planning for Physically-Embodied Agents using Realistic Human Motion Models, In Simulation and Gaming Journal, Mar 2008
20. Emulating Humans (Teamwork)
    • Reading: X. Fan and J. Yen. Realistic Cognitive Load Modeling for Enhancing Shared Mental Models in Human-Agent Collaboration. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-07)
21. No Class; Take-home Exam (Mar 27)
22. Student Paper Presentations (Apr 1-17th)
    • Apr 1 Presenter: Phillip Verbancsics, Paper: R. Pienaar and J. Kruger, An egocentric approach to machine intelligence
      Presenter: Bryan Rosander, Paper: A. Sanchez-Ruiz, S. Lee-Urban, H. Munoz-Avila, B. Diaz-Augdo, P. Gonzalez-Calera, Game AI for a Turn-based Strategy Game with Plan Adaptation and Ontology-based Retrieval
    • Apr 3 Presenter: Robert Hauser, Paper: T. Balch and M. Hybinette, Social Potentials for Scalable Multi-Robot Formations Proceedings of IEEE International Conference on Robotics and Automation, 2000
      Presenter: J.T. Folsom-Kovarik Paper: S. Whiteson, P. Stone Evolutionary Function Approximation for Reinforcement Learning, Journal of Machine Learning Research, 2006
    • Apr 8 Presenter: Dan DeBlasio, Paper: Uchibe, E.; Asada, M., Incremental Coevolution With Competitive and Cooperative Tasks in a Multirobot Environment, Proceedings of the IEEE , vol.94, no.7, pp.1412-1424, July 2006
      Presenter: Matt Meighan, Paper: E. Jones, B. Browning, M. Dias, B. Argall, M. Veloso, and A. Stentz, Dynamically Formed Heterogeneous Robot Teams Performing Tightly Coordinated Tasks International Conference on Robotics and Automation, May, 2006, pp. 570 - 575
    • Apr 10 Presenter: David Lyle, Paper: C. Scrapper, S. Balakirsky, and E. Messina, MOAST and USARSim- A Combined Framework for the Development and Testing of Autonomous Systems, Proceedings of the SPIE Defense and Security Symposium, 2006
      Presenter: Mikel Rodriguez, Paper: S. Bahadori and L. Iocchi, Human Body Detection in the RoboCup Rescue Scenario, Proc. Int. RoboCup Symposium, 2003
    • Apr 15 Presenter: Richard Lum, Paper: C. Yunpeng, C. Jiang, Y. Jinyi, and L. Shi, Global Planning from Local Perspective: An Implementation of Observation-based Plan Coordination in RoboCup Simulation Games, RoboCup 2001: Robot Soccer World Cup V
      Presenter: Craig Dean, Paper: MIT Urban Challenge Tech Report
      Presenter: Gautham Anil, Paper: R. Paul Wiegand, M. Potter, D. Sofge, and W. Spears, , A Generalized Graph-Based Method for Engineering Swarm Solutions to Multiagent Problems, Parallel Problem Solving from Nature PPSN IX, 2006
    • Apr 17 Presenter: John Reeder, Paper: Yuriy Nevmyvaka, Normative Approach to Market Microstructure Analysis (9.b.iii Pages 163 - 182), 2005
      Presenter: Siddharth S. Somvanshi, Paper: Baldassarre G., Parisi D., Nolfi S., Coordination and Behaviour Integration in Cooperating Simulated Robots In S. Schaal, A. Ijspeert, A. Billard, S. Vijayakumar, J. Hallam and J-A. Meyer (Eds.), From Animals to Animats 8: Proceedings of the VIII International Conference on Simulation of Adaptive Behavior, pp. 385-394. MIT Press, Cambridge, MA
23. Final Project Demos (Wed, Apr 23rd, HEC 111, 1-4pm)
    1:00-1:30 Gautham Anil, Siddharth Somvanshi
    1:30-1:45 Craig Dean
    1:45-2:00 David Lyle
    2:00-2:15 Dan deBlasio
    2:15-2:45 JT Folsom-Kovarik, Philip Verbancsics
    2:45-3:00 Robert Hauser
    3:00-3:15 Richard Lum
    3:15-3:30 Matt Meighan
    3:30-3:45 Bryan Rosander
    3:45-4:00 Mikel Rodriguez