Agents are computational entities that are situated in dynamic environments, acting to fulfill desired ends, and reacting to changing situations. Agents or, at least, an important subclass of agents, can be viewed as having mental states that comprise the beliefs, desires, plans, and intentions both of themselves and of others. While it is reasonable for us, as designers of multi-agent systems, to provide for an agent its own beliefs, desires, and plans (based on which it forms its intentions), it is quite natural for the agents then to recognize the beliefs, desires, plans, and intentions of the other agents in its environment. There has been considerable work in recent years on plan recognition [9, 11] that focuses on inferring the plans and intentions of other agents. However, most of this work treats plan recognition as the reverse process of classical planning, concerned with inferring plans .262
Characters are a critical part of storytelling and emotion is a vital part of character. Readers generally credit characters with human emotions, and it is these emotions which bring meaning to stories. To computationally construct interesting and meaningful stories we need a model of emotion which allows us to predict characters’ reactions to events in the world. There are many different psychological theories of emotion; the most popular to date for computational applications is the OCC theory. This paper describes a Discrete Event Calculus implementation of the OCC Theory of Emotion. To evaluate our system, we apply it to a selection of Aesop’s fables, and compare the output to the emotions readers expect in the same situations based on a survey.
The safety of our online lives has become increasingly important. Whether it be interference in elections, attacks by hostile forces, or online fraud, the security of the web feels fragile. Cybersecurity has reached a crossroads and we need to decide where it goes next. The outcome will touch each of us – will we pay more and yet still be less safe? Will we face higher insurance premiums and bank charges to cover the rising number of cyber-incidents?
This paper describes a framework for modeling emotions in an interactive, decision-making agent. In tune with modern theories of emotions (e.g., Damasio, 1995; LeDoux, 1992), we regard emotions essentially as subconscious signals and evaluations that inform, modify, and receive feedback from a variety of sources including higher cognitive processes and the sensorimotor system.