SEA 2014 - 3rd International Workshop on Self-Explaining Agents
Date2014-09-22 - 2014-09-26
Deadline2014-04-22
VenueStuttgart, Germany
Keywords
Websitehttps://sea.dai-labor.de
Topics/Call fo Papers
Self-Explaining systems have the ability to describe their functionality in a context depending and structured way. Self-explanatory descriptions thus help reasoners to better understand these systems. Becoming more self-explanatory requires not only work on the descriptions, the used languages and description paradigms but also on the reasoners, which utilize such descriptions and tools to create them. This places the research questions of this workshop in between the Service, the Agent and the Artificial Intelligence community.
Services and their descriptions have been well researched and researchers investigated languages like OWL and OWL-S. Such languages are used to describe functionality which enables reusability and adaptability of service oriented architectures with reasoners like FACT++ or Pellet. This is one reason why service descriptions become more self-explanatory these days.
Agents on the other hand use less self-explanatory description. The agent community focus on developing more sophisticated planning algorithms (e.g., Fast Downward Stone Soup) and heuristics to select the right functionality to become part of the plan.
Both paradigms cope with situations where complex systems are build upon descriptions of functionalities, which are more or less self-explanatory. Artificial Intelligent reasoners are used to analyze those descriptions and reason whether the functionality satisfies a given requests or preconditions and effects. Combining the strong suits of both research areas, bear opportunities for self-explaining agents.
This workshop analyzes state-of-the-art in regards to the use of self-explanatory descriptions used by service matcher, agent planner as well as how to extract heuristics by reasoning upon self-explanatory descriptions and semantic description language with the goal of building more loosely coupled, dynamic and adaptive software. Thus we welcome practical applications as well as theoretical foundations as contributions for this workshop.
Services and their descriptions have been well researched and researchers investigated languages like OWL and OWL-S. Such languages are used to describe functionality which enables reusability and adaptability of service oriented architectures with reasoners like FACT++ or Pellet. This is one reason why service descriptions become more self-explanatory these days.
Agents on the other hand use less self-explanatory description. The agent community focus on developing more sophisticated planning algorithms (e.g., Fast Downward Stone Soup) and heuristics to select the right functionality to become part of the plan.
Both paradigms cope with situations where complex systems are build upon descriptions of functionalities, which are more or less self-explanatory. Artificial Intelligent reasoners are used to analyze those descriptions and reason whether the functionality satisfies a given requests or preconditions and effects. Combining the strong suits of both research areas, bear opportunities for self-explaining agents.
This workshop analyzes state-of-the-art in regards to the use of self-explanatory descriptions used by service matcher, agent planner as well as how to extract heuristics by reasoning upon self-explanatory descriptions and semantic description language with the goal of building more loosely coupled, dynamic and adaptive software. Thus we welcome practical applications as well as theoretical foundations as contributions for this workshop.
Other CFPs
Last modified: 2014-02-15 10:41:27