The affective reasoner: a process model of emotions in a multi-agent system
The affective reasoner: a process model of emotions in a multi-agent system
C4.5: programs for machine learning
C4.5: programs for machine learning
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension
In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension
Machine Learning
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
Emotional Behavior: A Resource Management Approach
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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There are several approaches to emotions in AI, most of which are inspired by human emotional states and their arousal mechanisms. These approaches usually use high-level models of human emotions that are too complex to be directly applicable in simple artificial systems. It seems that a new approach to emotions, based on their functional role in information processing in mind, can help us to construct models of emotions that are both valid and simple. In this paper, we will try to present a model of emotions based on their role in controlling the attention. We will evaluate the performance of the model and show how it can be affected by some structural and environmental factors.