We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
We consider apprenticeship learning—learning from expert demonstrations—in the setting of large, complex domains. Past work in apprenticeship learning requires that the expert...
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
Enhancing the service-oriented architecture paradigm with semantic components is a new field of research and goal of many ongoing projects. The results lead to more powerful web a...
Recent studies by agriculture researchers in Pakistan have shown that attempts of crop yield maximization through pro-pesticide state policies have led to a dangerously high pesti...