Towards a standard upper ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Negotiation over tasks in hybrid human-agent teams for simulation-based training
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Simulating adaptive communication
Simulating adaptive communication
Discourse obligations in dialogue processing
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Integrated Models of Cognitive Systems (Advances in Cognitive Models and Architectures)
Integrated Models of Cognitive Systems (Advances in Cognitive Models and Architectures)
Spatial representation and reasoning for human-robot collaboration
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Incorporating mental simulation for a more effective robotic teammate
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Overgeneration and ranking for spoken dialogue systems
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
Mechanisms for human spatial competence
SC'06 Proceedings of the 2006 international conference on Spatial Cognition V: reasoning, action, interaction
The synthetic teammate project
Computational & Mathematical Organization Theory
Abstraction, imagery, and control in cognitive architecture
Abstraction, imagery, and control in cognitive architecture
The best papers from BRIMS 2011: models of users and teams interacting
Computational & Mathematical Organization Theory
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The ability to coherently represent information that is situationally relevant is vitally important to perform any complex task, especially when that task involves coordinating with team members. This paper introduces an approach to dynamically represent situation information within the ACT-R cognitive architecture in the context of a synthetic teammate project. The situation model represents the synthetic teammate's mental model of the objects, events, actions, and relationships encountered in a complex task simulation. The situation model grounds textual information from the language analysis component into knowledge usable by the agent-environment interaction component. The situation model is a key component of the synthetic teammate as it provides the primary interface between arguably distinct cognitive processes modeled within the synthetic teammate (e.g., language processing and interactions with the task environment). This work has provided some evidence that reasoning about complex situations requires more than simple mental representations and requires mental processes involving multiple steps. Additionally, the work has revealed an initial method for reasoning across the various dimensions of situations. One purpose of the research is to demonstrate that this approach to implementing a situation model provides a robust capability to handle tasks in which an agent must construct a mental model from textual information, reason about complex relationships between objects, events, and actions in its environment, and appropriately communicate with task participants using natural language. In this paper we describe an approach for modeling situationally relevant information, provide a detailed example, discuss challenges faced, and present research plans for the situation model.