Temporal reasoning in artificial intelligence

@inproceedings{Shoham1988TemporalRI,
  title={Temporal reasoning in artificial intelligence},
  author={Yoav Shoham and Nitakshi Goyal},
  year={1988}
}
Temporal Reasoning and Problem Solving
TLDR
A temporal framework that combines the advantages of both the point-based and the interval-based systems which allow metric bounds on an event's duration is developed and an efficient algorithm for propagating temporal constraints is developed.
Modeling a Dynamic and Uncertain World I: Symbolic and Probabilistic Reasoning About Change
Dynamic Reasoning Systems
TLDR
The general notion of a DRS comprises a framework within which one can formulate the logic and algorithms for a given application and prove that the algorithms are correct, that is, that they serve to derive all salient information and preserve the consistency of the belief set.
Reasoning About Action and Change
TLDR
This chapter presents the state of research concerning the formalisation of an agent reasoning about a dynamic system which can be partially observed and acted upon, and addresses a special case of progression, namely belief update.
Reasoning About Indefinite Actions
TLDR
This paper views planning as a special case of reasoning about indefinite actions, and proposes a formalization of this problem using circumscription, and argues that this is the correct formalization if the authors' action definitions include recursive rules.
Models in Temporal Knowledge Representation and Temporal DBMS (90-8)
TLDR
The Al research is expected to help to understand the problems of temporal reasoning (how do the authors draw conclusions from time related facts) and the conceptual representation of temporal data in GIS.
Microprocessor systems diagnosis using a time-range approach
TLDR
The concept of time range is proposed as a key component of an enhanced time structure which captures the notion of time impreciseness in event occurrence.
Time for Action: On the Relation Between Time, Knowledge and Action
TLDR
This work considers the role played by the concept of action in AI, and proposes a framework that retains the advantages of both viewpoints, and that ties the notion of action closely to that of knowledge.
Rational control of reasoning in Artificial Intelligence
  • J. Doyle
  • Psychology
    The Logic of Theory Change
  • 1989
TLDR
It is shown how some of the means by which artificial reasoners tolerate and even exploit limitations in carrying out basic cognitive tasks may all be viewed as species of rationally guided or controlled reasoning, or more generally, as forms of rational self-government.
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References

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A taxonomy of important binary relations between intervals which are unions of convex intervals, and examples of these relations applied to the description of tasks and events are provided.
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TLDR
The salient features of a new system for reasoning about time that represents time primarily — though not exclusively — in terms of intervals, and performs deductions on this representation has a mechanism for maintaining consistency in the representation and discovering the origin of inconsistencies.
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TLDR
The possible-worlds semantics for propositional logics of knowledge and belief is reviewed and it is shown that while the problem of deciding satisfiability of an S5 formula with one knower is NP-complete, the problem for many knowers is PSPACE-complete.
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TLDR
An appropriate axiom system is given which is complete for loop-free programs and also puts conventional predicate calculus in a different light by lumping quantifiers with non-logical assignments rather than treating them as logical concepts.
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