Abstract
Autonomous intelligent agents have become a very important research area in Artificial Intelligence (AI). Socio-cultural situations are one challenging area in which autonomous intelligent agents can acquire new knowledge or modify existing one. Socio-cultural situations can be best represented in the form of cognitive scripts that can allow different techniques to be used to facilitate knowledge transfer between scripts. Conceptual blending has proven successful in enhancing the social dynamics of cognitive scripts, where information is transferred from similar contextual scripts to a target script resulting in a new blended script. To the extent of our knowledge, there is no computational model available to evaluate these newly generated cognitive scripts. This work aims to develop a computational model to evaluate cognitive scripts resulting from blending two or more linear cognitive scripts. The evaluation process involves: 1) using the GloVe similarity to check if the transferred events conceptually fit the target script; 2) using the semantic view of text coherence to decide on the optimal position(s) to place the transferred event(s) in the target script. Results show that the GloVe similarity can be applied successfully to preserve the contextual meaning of cognitive scripts. Additional results show that GloVe embedding gives higher accuracy over Universal Sentence Encoder (USE) and Smooth Inverse Frequency (SIF) embedding but this comes with a high computational cost. Future work will look into reducing the computational cost and enhancing the accuracy.
Highlights
Autonomous intelligent agents are a very important research area in Artificial Intelligence (AI)
This seems to be quite difficult in some domains, such as sociocultural situations because of the temporal and causal relations twined in these situations
We live in a world consisting of objects and events that relate these objects to each other. People store their knowledge about socio-cultural situations as a sequence of events, such as ―Entering a restaurant‖ or ―Attending a lecture‖ situations. Such socio-cultural situations are best represented in the form of cognitive scripts with events connected by directional edges
Summary
Autonomous intelligent agents are a very important research area in Artificial Intelligence (AI). Intelligent agents possessing mental abilities, such as knowledge, belief, intention, and obligation can have human-like capabilities, such as artificial intuition and imagination, analogy and conceptual blending, design, writing poetry, argumentation, dialogue generation, negotiation abilities and shared mental models It is important for autonomous intelligent agents to be able to acquire new knowledge or modify existing one. People think of a situation as a sequence of routine actions/events that can be represented in the form of cognitive scripts These events are connected temporally or causally with preceding and succeeding events [1]. A cognitive script may be linear or multi-branched as shown in Fig. 1 in which each path in the multi-branched script can be seen as an independent linear script [1] In this figure, the cinema cognitive script consits of different events such as ―Audience buys ticket‖, ―Lights off‖, and ―Audience watches movie‖. These paths have three interscting events; ―Audience enters auditorium‖, ―audience watches movie‖ and ―Movie ends‖
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