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AGENTS
1999
Springer
15 years 2 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
WWW
2009
ACM
15 years 10 months ago
Adaptive bidding for display advertising
Motivated by the emergence of auction-based marketplaces for display ads such as the Right Media Exchange, we study the design of a bidding agent that implements a display adverti...
Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Va...
AI
2007
Springer
14 years 10 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
AI
2008
Springer
14 years 10 months ago
Strategic bidding in continuous double auctions
In this paper, we describe a novel bidding strategy that autonomous trading agents can use to participate in Continuous Double Auctions (CDAs). Our strategy is based on both short...
Perukrishnen Vytelingum, Dave Cliff, Nicholas R. J...
ICMLA
2008
14 years 11 months ago
A Predictive Model for Imitation Learning in Partially Observable Environments
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
Abdeslam Boularias