no code implementations • 9 May 2023 • Keyang He, Prashant Doshi, Bikramjit Banerjee
There is a prevalence of multiagent reinforcement learning (MARL) methods that engage in centralized training.
no code implementations • 17 Jun 2021 • Keyang He, Prashant Doshi, Bikramjit Banerjee
Recent renewed interest in multi-agent reinforcement learning (MARL) has generated an impressive array of techniques that leverage deep reinforcement learning, primarily actor-critic architectures, and can be applied to a limited range of settings in terms of observability and communication.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 15 Oct 2020 • Keyang He, Bikramjit Banerjee, Prashant Doshi
As such, the individual agent in the organization must cooperate and compete.
1 code implementation • 27 Apr 2020 • Saurabh Arora, Bikramjit Banerjee, Prashant Doshi
The learner aims to learn the multiple reward functions that guide these ways of solving the problem.
no code implementations • 21 May 2018 • Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
Inverse reinforcement learning (IRL) is the problem of learning the preferences of an agent from the observations of its behavior on a task.