Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Learning to Co-operate in Multi-Agent Systems Experiments with the RoboCup Simulator

Learning to Co-operate in Multi-Agent Systems Experiments with the RoboCup Simulator

Kostiadis, Kostas

Paperback

General Computers

ISBN10: 3639102592
ISBN13: 9783639102598
Publisher: Blues Kids Of Amer
Published: Dec 16 2008
Pages: 156
Weight: 0.48
Height: 0.33 Width: 6.00 Depth: 9.00
Language: English
In recent years, two major areas of computer science have started converging. Artificial intelligence research is moving towards realistic domains requiring real-time responses, and real-time systems are moving towards more complex applications requiring intelligent behaviour. This book addresses the question of whether agents can learn to become individually skilled and also learn to co-operate in the presence of both teammates and adversaries in a complex, real-time, noisy environment with no communication. To answer this question this work starts by presenting a multi-threaded agent architecture capable of dealing with the logical and timing challenges of such an environment. The decision making process is broken down into simple modules that link together an agent's perception to its actions. The book demonstrates how a sparse distributed memory model can be used as a generalisation component for tasks that involve large state spaces. It further demonstrates how reinforcement learning can be linked to such a memory model and produce intelligent action. Experimental results demonstrate how a learned policy can outperform fixed, hand-coded ones.

Also in

General Computers

View All