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Found 2 papers, 1 papers with code
Reward Design for Justifiable Sequential Decision-Making
In this work, we propose the use of a debate-based reward model for reinforcement learning agents, where the outcome of a zero-sum debate game quantifies the justifiability of a decision in a particular state.
Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs
These challenges are particularly prominent in the context of multi-agent sequential decision-making, where the causal effect of an agent's action on the outcome depends on how other agents respond to that action.
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