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Andre Beckus

2 accepted papers

2021

Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search

AAAI 2021technical

Reinforcement learning and planning have been revolutionized in recent years, due in part to the mass adoption of deep convolutional neural networks and the resurgence of powerful methods to refine decision-making policies. However, the problem of sparse reward signals and their representation remai…

Cited by 22SourcePDFScholar
2020

Steady-State Policy Synthesis in Multichain Markov Decision Processes

IJCAI 2020poster

The formal synthesis of automated or autonomous agents has elicited strong interest from the artificial intelligence community in recent years. This problem space broadly entails the derivation of decision-making policies for agents acting in an environment such that a formal specification of behavi…

Cited by 0SourcePDFScholar