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Co-Learning Empirical Games and World Models
We investigate the potential gain from co-learning these elements: a world model for dynamics and an empirical game for strategic interactions.
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
Multiagent reinforcement learning (MARL) has benefited significantly from population-based and game-theoretic training regimes.
Multiattribute Auctions Based on Generalized Additive Independence
We develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences.
Qualitative Probabilistic Networks for Planning Under Uncertainty
Bayesian networks provide a probabilistic semantics for qualitative assertions about likelihood.
The Role of Calculi in Uncertain Inference Systems
Architectures for uncertainty handling that take statements in the calculus as objects to be reasoned about offer the prospect of retaining normative status with respect to decision making while supporting the other tasks in uncertain reasoning.
Exploiting Functional Dependencies in Qualitative Probabilistic Reasoning
Functional dependencies restrict the potential interactions among variables connected in a probabilistic network.
