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TDDD10 AI Programming

Timetable


Period 1

The schedule for the first period of the course is available from the schedule server.

Week 35 (27/8 - 31/8)
Mo 08-10 P34 Le 1 Cyrille Introduction to the course, to RoboCup, and the Soccer Server, slides [PDF].
 
Tu 13-17 SU14 La 1-2 Cyrille Practical introduction to RoboCup and RoboSoc
 
We 10-12 R37 Le 2 Cyrille Implementing Skills in RoboSoc, slides [PDF].
  • R. de Boer and J.R. Kok. The Incremental Development of a Synthetic Multi-Agent System: The UvA Trilearn 2001 Robotic Soccer Simulation Team. Master's thesis, University of Amsterdam, The Netherlands, feb 2002 [PDF]
  • F. Heintz. The RoboSoc Manual [PDF].
 
Th 17-21 SU14 La 3-4 Cyrille
 
 
Week 36 (3/9 - 7/9)
Mo 08-10 P34 Le 3 Cyrille Agents and Agent Architectures, slides [PDF].
  • Chapters 1-5 in the course book.
Almost equivalent to chapter 1 and 2:
  • Michael Wooldridge, Intelligent Agents in G. Weiss, editor: Multiagent Systems, The MIT Press, April 1999, [PDF]
Almost equivalent to section 3.2:
  • Yoav Shoham, Agent Oriented Programming, Journal of Artificial Intelligence , 60(1), pp.51-92, 1993
Almost equivalent to chapter 5:
  • Erann Gat, On Three-Layer Architectures, 1998, [PS]
 
Tu 13-17 SU14 La 5-6 Cyrille
 
Fr 8-10 R34 Le 4 Cyrille Multiagent systems I: Introduction and Communication, slides [PDF].
  • Katia Sycara, MultiAgent Systems, 1998, [PDF]
  • P. Stone and M. Veloso, Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork, 1999, [PDF]
  • Chapters 6 and 7 in the course book.
Almost equivalent to chapter 7:
  • Y. Labrou, T. Finin, and Y. Peng, Agent Communication Languages: The Current Landscape, 1999, [PDF]
 
Week 37 (10/9 - 14/9)
Mo 08-10 P36 Le 5 Cyrille Multiagent systems II: Multiagent Decision Making, slides [PDF].
  • Chapters 11-13 in the course book.
 
Tu 13-17 SU14 La 7-8 Cyrille
 
Fr 8-10 P36 Le 6 Cyrille Multiagent Systems III: Cooperation and Coordination, slides [PDF].
  • Chapters 8, 14, and 15 in the course book.
 
Week 38 (17/9 - 21/9)
Mo 08-10 P36 Le 7 Cyrille Machine Learning I, slides [PDF].
 
Tu 13-17 SU14 La 9-10 Cyrille
 
We 10-12 R37 Se 1 Cyrille
Discuss skill assignment. Each group is supposed to present their approach to implementing the skills in the skill assignment. The idea is to provide feedback on current approaches and to find even better solutions together. It is also a perfect opportunity to ask questions about the skill assignment.
 
Th 17-21 SU14 La 11-12 Cyrille
 
Week 39 (24/9 - 29/9)
Mo 08-10 P34 Le 8 Cyrille Machine Learning II, slides [PDF].
 
Tu 13-17 SU14 La 13-14 Cyrille
 
We 10-12 R36 Le 9 Cyrille
Knowledge Representation and Opponent Modeling, slides [PDF].
  • L. Vila, A Survey on Temporal Reasoning in Artificial Intelligence, AI Communications, vol 7 pp 4-28, 1994.
  • C. Luca and M. Angelo, Temporal representation and reasoning in artificial intelligence: Issues and approaches, Annals of Mathematics and Artificial Intelligence, vol 28 pp 47-106, 2000. [PDF]
  • R. Dechter, I. Meiri, and J. Pearl, Temporal constraint networks, Journal of Artificial Intelligence, vol 49 pp 61-95, 1991.
  • J. F. Allen, Towards a General Theory of Action and Time, Journal of Artificial Intelligence, vol 23 pp 123-154, 1984.
  • Parsons, S. and Hunter, A., A review of uncertainty handling formalisms, in Applications of uncertainty formalisms (A. Hunter and S. Parsons, eds.) Springer Verlag, 1998, [PS, PDF]
  • P. Stone, P. Riley, and M. Veloso, Defining and Using Ideal Teammate and Opponent Agent Models, 2000, [PS]
 
Week 40 (1/10 - 5/10)
Mo 08-10 P34 Le 10 Cyrille
AI Programming - Putting it all together, slides [PDF].
 
Tu 13-17 SU14 La 15-16 Cyrille
 
We 10-12 R36 Se 2 Cyrille
Discuss multiagent systems. It is not obvious how to take theory about multiagent systems and apply it to RoboCup. One goal of this seminar is to discuss how theories and approaches presented at the lectures can be used in RoboCup. The purpose is to reduce the gap between theory and practice. During the seminar we will also discuss what abstractions would be nice to have when implementing the solutions in RoboCup.
Summary from HT2007:
 
Th 17-21 SU14 La 17-18 Cyrille
 
Week 42 (16/10 - 17/10)
Tu 13-17 SU14 La 19-20 Cyrille
 
We 10-12 P36 Se 3 Cyrille
Discuss machine learning. There are many practical issues when trying to use machine learning approaches in RoboCup. For example, how to collect good training data for neural networks or how to create a small and representative state space for reinforcement learning. Since many groups choose to work on machine learning it seems relevant to have a seminar where we can discuss these issues. Summary of discussion from HT2008: [PDF].

Period 2

The schedule for the second period of the course is available from the schedule server.

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Page responsible: Fredrik Heintz
Last updated: 2012-08-30