Unified theories of cognition
Extending the Soar Cognitive Architecture
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Towards a validated model of "emotional intelligence"
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Affective negotiation support systems
Journal of Ambient Intelligence and Smart Environments
Computational modeling of brain processes for agent architectures: issues and implications
BI'11 Proceedings of the 2011 international conference on Brain informatics
Emotion generation integration into cognitive architecture
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
An integrative computational model of emotions
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
BI'12 Proceedings of the 2012 international conference on Brain Informatics
Cognitive Computational Models of Emotions and Affective Behaviors
International Journal of Software Science and Computational Intelligence
Using Emotional Intelligence in Training Crisis Managers: The Pandora Approach
International Journal of Distance Education Technologies
Affective and cognitive design for mass personalization: status and prospect
Journal of Intelligent Manufacturing
An emotion understanding framework for intelligent agents based on episodic and semantic memories
Autonomous Agents and Multi-Agent Systems
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Existing models that integrate emotion and cognition generally do not fully specify why cognition needs emotion and conversely why emotion needs cognition. In this paper, we present a unified computational model that combines an abstract cognitive theory of behavior control (PEACTIDM) and a detailed theory of emotion (based on an appraisal theory), integrated in a theory of cognitive architecture (Soar). The theory of cognitive control specifies a set of required computational functions and their abstract inputs and outputs, while the appraisal theory specifies in more detail the nature of these inputs and outputs and an ontology for their representation. We argue that there is a surprising functional symbiosis between these two independently motivated theories that leads to a deeper theoretical integration than has been previously obtained in other computational treatments of cognition and emotion. We use an implemented model in Soar to test the feasibility of the resulting integrated theory, and explore its implications and predictive power in several task domains.