1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.AI2020
Integrating Acting, Planning and Learning in Hierarchical Operational Models
Sunandita Patra, James Mason, Amit Kumar +3
We present new planning and learning algorithms for RAE, the Refinement Acting Engine. RAE uses hierarchical operational models to perform tasks in dynamically changing environment…
cs.AI2019★ 1 cited
Incremental Learning of Discrete Planning Domains from Continuous Perceptions
Luciano Serafini, Paolo Traverso
We propose a framework for learning discrete deterministic planning domains. In this framework, an agent learns the domain by observing the action effects through continuous featur…
cs.AI2018
Incremental learning abstract discrete planning domains and mappings to continuous perceptions
Luciano Serafini, Paolo Traverso
Most of the works on planning and learning, e.g., planning by (model based) reinforcement learning, are based on two main assumptions: (i) the set of states of the planning domain…