A semantic-based flexible framework for automatic behavior composition
Autor: | Richard St-Denis, Masoud Barati |
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Rok vydání: | 2015 |
Předmět: |
Computer science
business.industry media_common.quotation_subject Controller (computing) Machine learning computer.software_genre Semantics Semantic similarity Human–computer interaction Semantic computing Artificial intelligence Automatic behavior Set (psychology) Function (engineering) business computer Drawback media_common |
Zdroj: | 2015 Internet Technologies and Applications (ITA). |
DOI: | 10.1109/itecha.2015.7317380 |
Popis: | The behavior composition problem consists in the synthesis of a controller that coordinates a set of available behaviors with the aim of realizing a desired target behavior. This problem suffers from a serious drawback because, for many instances, the target behavior cannot be achieved. In that case, the user is responsible for bringing changes until the problem becomes solvable. This inherent limitation is due to the fact that an exact match is required between the actions initiated by the user and those offered by the available behaviors. The main question is, how can a controller select a suitable behavior such that the functionality of one of its available actions is close to that currently requested by the desired target behavior? This paper provides an answer to this question by associating semantics to actions based on expectations and exploiting a semantic similarity function between actions. Similar actions that have different names, but comparable tasks, are considered equivalent. This renders the behavior composition framework more flexible so that it can fit with semantic environments. |
Databáze: | OpenAIRE |
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