52,475 research outputs found
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Analysis and design of multiagent systems using MAS-CommonKADS
This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network
Towards A Theory-Of-Mind-Inspired Generic Decision-Making Framework
Simulation is widely used to make model-based predictions, but few approaches
have attempted this technique in dynamic physical environments of medium to
high complexity or in general contexts. After an introduction to the cognitive
science concepts from which this work is inspired and the current development
in the use of simulation as a decision-making technique, we propose a generic
framework based on theory of mind, which allows an agent to reason and perform
actions using multiple simulations of automatically created or externally
inputted models of the perceived environment. A description of a partial
implementation is given, which aims to solve a popular game within the
IJCAI2013 AIBirds contest. Results of our approach are presented, in comparison
with the competition benchmark. Finally, future developments regarding the
framework are discussed.Comment: 7 pages, 5 figures, IJCAI 2013 Symposium on AI in Angry Bird
On Agent-Based Software Engineering
Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and the practice of modeling, designing, and implementing computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. Moreover, even less effort has been devoted to discussing the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures
Towards engineering ontologies for cognitive profiling of agents on the semantic web
Research shows that most agent-based collaborations
suffer from lack of flexibility. This is due to the fact that
most agent-based applications assume pre-defined
knowledge of agents’ capabilities and/or neglect basic
cognitive and interactional requirements in multi-agent
collaboration. The highlight of this paper is that it brings
cognitive models (inspired from cognitive sciences and HCI)
proposing architectural and knowledge-based requirements
for agents to structure ontological models for cognitive
profiling in order to increase cognitive awareness between
themselves, which in turn promotes flexibility, reusability
and predictability of agent behavior; thus contributing
towards minimizing cognitive overload incurred on humans.
The semantic web is used as an action mediating space,
where shared knowledge base in the form of ontological
models provides affordances for improving cognitive
awareness
Introduction to the Special Issue: The AgentLink III Technical Forums
This article introduces the special issue of ACM Transactions on Autonomous and Adaptive Systems devoted to research papers arising from the three Technical Forum Group meetings held in 2004 and 2005 that were organized and sponsored by the European FP6 Coordination Action AgentLink III
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