The use of a blackboard system for story processing by computer
One of the major objectives in story understanding is to discover the causal reasoning behind characters' actions and to link these into an overall picture of the characters' motivations and actions. Thus the main aim when processing a sentence is to discover a character's goal in which this sentence can be considered as a step towards its achievement. The above process uses abductive reasoning in drawing its inferences and as a consequence of this any facts that are derived from a sentence might be invalid, causing a number of facts to be generated that are inconsistent with the knowledge base. A further complication to story understanding is that much of the information that is necessary for understanding to occur can only be obtained using default reasoning. Any such default fact remain valid unless a further statement proves that this is not the case. As a consequence of the above any new statements must be check against the rest of the knowledge base to make sure there are no inconsistencies and a list of supporting statements must be held so that any inconsistency found can be resolved and erased. An alternative to erasing these inconsistent statements within the knowledge base is to maintain a number of consistent environments using an assumption based truth maintenance system to enforce consistency. This has the advantage that more than one environment may be worked on at once and environments can be compared. The thesis discusses the maintenance of more than one environment and proposes a blackboard system, along with an assumption based truth maintenance system, as an ideal architecture to support the requirements of a story understanding program. The thesis also describes the knowledge sources, such as syntax and semantics, that are necessary for story understanding and how their operation should be controlled using a dynamic scheduling system.