Towards a general theory of action and time
Artificial Intelligence
| Hi-index | 0.00 |
This paper describes a system that performs Temporal Event Recognition, ie., the task of forming causal and conceptual descriptions of stimulii given to a system over a period of time. A temporal logic that integrates state based and interval based representations is is used to represent and maintain knowledge about the temporal relationships between events. A knowledge based system is then constructed that uses this temporal knowledge to generate higher level conceptual abstractions that describe the events occurring at the input. An implementation of the system called MUSE is described and examples of the system working in a Blocks world are presented.