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Found 5 papers, 0 papers with code
Integrating Disambiguation and User Preferences into Large Language Models for Robot Motion Planning
To enhance the reliability of LLMs in the framework and improve user experience, we propose methods to resolve the ambiguity in natural language instructions and capture user preferences.
Epidemic Population Games And Perturbed Best Response Dynamics
This paper proposes an approach to mitigate epidemic spread in a population of strategic agents by encouraging safer behaviors through carefully designed rewards.
Learning with Delayed Payoffs in Population Games using Kullback-Leibler Divergence Regularization
Their goal is to learn the strategies of the Nash equilibrium of the game.
Payoff Mechanism Design for Coordination in Multi-Agent Task Allocation Games
As key contributions, we propose a method to find a payoff-driven decision-making model, and discuss how the model allows the strategy selection of the agents to be responsive to the amount of remaining jobs in each task while asymptotically attaining the optimal strategies.
Tuning Rate of Strategy Revision in Population Games
In particular, when the time delays are large, the strategy revision would exhibit oscillation and the agents spend substantial time in "transitioning" between different strategies, which prevents the agents from attaining the Nash equilibrium of the game.
