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» A Game-Theoretic Approach to Apprenticeship Learning
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ATAL
2011
Springer
12 years 7 months ago
Game theory-based opponent modeling in large imperfect-information games
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
Sam Ganzfried, Tuomas Sandholm
JUCS
2008
104views more  JUCS 2008»
13 years 7 months ago
Optimal Transit Price Negotiation: The Distributed Learning Perspective
: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmi...
Dominique Barth, Loubna Echabbi, Chahinez Hamlaoui
UAI
2004
13 years 9 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
AAAI
2008
13 years 10 months ago
Perpetual Learning for Non-Cooperative Multiple Agents
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
Luke Dickens
PRESENCE
2006
104views more  PRESENCE 2006»
13 years 7 months ago
Physically Realistic Virtual Surgery Using the Point-Associated Finite Field (PAFF) Approach
The generation of multimodal virtual environments for surgical training is complicated by the necessity to develop heterogeneous simulation scenarios such as surgical incision, ca...
Suvranu De, Yi-Je Lim, Manivannan Muniyandi, Manda...