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» The Computational Complexity of Agent Design Problems
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SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
15 years 10 months ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen
137
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AAMAS
2008
Springer
15 years 3 months ago
Logic-based automated multi-issue bilateral negotiation in peer-to-peer e-marketplaces
Abstract. We present a novel logic-based framework to automate multi-issue bilateral negotiation in e-commerce settings. The approach exploits logic as communication language among...
Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciasc...
IJAR
2008
118views more  IJAR 2008»
15 years 3 months ago
Dynamic multiagent probabilistic inference
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Xiangdong An, Yang Xiang, Nick Cercone
AAMAS
2010
Springer
15 years 3 months ago
Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs
POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
KER
2008
193views more  KER 2008»
15 years 3 months ago
The 1st international workshop on computational social choice
Computational social choice is a new discipline currently emerging at the interface of social choice theory and computer science. It is concerned with the application of computati...
Ulle Endriss