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Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Eighth International Conference ♦ Reactive Answer Set Programming ♦ Autonomous System Action Learning ♦ Preliminary Report ♦ Reactive Asp ♦ Automatic Induction ♦ Effective Tool ♦ Abstract Action Learning ♦ Answer Set Programming ♦ Different Approach ♦ Sensoric Noise ♦ Real-time Induction ♦ Action Learning ♦ Action Model ♦ Conditional Effect ♦ Compact Knowledge Encoding ♦ Domain Dynamic ♦ Significant Advantage
Abstract Abstract—Action learning is a process of automatic induction of knowledge about domain dynamics. The idea to use Answer Set Programming (ASP) for the purposes of action learning has already been published in [2]. However, in reaction to latest introduction of Reactive ASP and implementation of effective tools [6], we propose a slightly different approach, and show how using the Reactive ASP together with more compact knowledge encoding can provide significant advantages. The technique proposed in this paper allows for real-time induction of action models in larger domains, and can be easily modified to deal with sensoric noise and non-determinism. On the other hand, it lacks the ability to learn the conditional effects. Keywords-ASP; learning; actions; induction;. I.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article