Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems

By A. Andrew. 2002

1,236 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Mathematical Physics

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Citations in the corpus

Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds (2017, methodology): “Such programs can be seen as partial iterative policies [Reiter, 2001].”
Reasoning about Probabilities in Unbounded First-Order Dynamical Domains (2017, methodology): “The BHL account is an extension to Reiter’s reworking of the situation calculus [Reiter, 2001].”
The Situation Calculus: A Case for Modal Logic (2010, methodology): “Besides knowledge and time, which we will turn to in a moment, there have been a number of other extensions of the situation calculus, dealing with issues like concurrency [44] or probabilities [1].”
Ltd Registered in England and Wales Registered Number : 1072954 Registered office : (2004, background): “, Rips (1994), and the semantic approach (based on construction of mental models), e.”
PREGO: An Action Language for Belief-Based Cognitive Robotics in Continuous Domains (2014, result): “Thus, we differ from these and many others (Poole 1998; Mateus et al. 2001; Grosskreutz and Lakemeyer 2003b; 2003a) in being able to address continuity in a general way, except for (Belle and Levesque 2013a) that we build on.”
Coherence and Flexibility in Dialogue Games for Argumentation (2005, background): “Finally, Brewka [8] has studied in detail how protocols for multi-party dialogues with a referee can be formalized in Reiter’s variant of the situation calculus [32].”
Understanding script-based stories using commonsense reasoning (2004, methodology): “We assess the portability of the system by extending it to handle 10 scripts frequent in Project Gutenberg American literature texts.”
Adapting Golog for Composition of Semantic Web Services (2002, methodology): “While [7] and [22] advocate the use of an online interpreter to reason with sensing actions, [13] suggests the use of an offline interpreter with conditional plans.”
Web Service Modeling Ontology (2005, neutral): “Slightly ‘abusing’ a situation calculus style notation (cf. for instance (Reiter, 2001)), given the state s 0 before executing the Web service and do ( service, s 0 ) the state after executing the Web service, we could write down the relation between these formulae as follows: Note that this…”
HTN planning for Web Service composition using SHOP2 (2004, background): “Narayanan and McIlraith [9] give a formal semantics for OWL-S in terms of the situation calculus [10] and Golog [11].”
Reasoning about Deterministic Actions with Probabilistic Prior and Application to Stochastic Filtering (2010, methodology): “Current approaches to probabilistic ﬁltering with PDDL or situation calculus (e.g., (Reiter 2001; Bacchus, Halpern, and Levesque 1999; Hajishirzi and Amir 2008)) use traditional ﬁltering methods as subroutines for reasoning about sequences of deterministic actions with probabilistic priors.”
A Logical Theory of Localization (2015, methodology): “These conventions are used for convenience only, and do not require any extension to the version of the formalism introduced in [46].”
Automatic Composition of Transition-based Semantic Web Services with Messaging (2005, result): “This is similar to the family of “fluents” found in semantic web services models such as OWL-S [15, 14], and more generally, found in situation calculii [17].”
Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches (2015, background): “cial Intelligence, such as situation calculus [64], IndiGolog [17] and classical planning.”
The scope and limits of simulation in automated reasoning (2016, background): “Simulation theories, might at first blush seem to be immune to the so-called frame problem – of efficiently reasoning about the aspects of a situation that do not change over time– that has often bedeviled knowledge-based theories [44]; in reality, the frame problem arises in simulation in very much”
On Progression and Query Evaluation in First-Order Knowledge Bases with Function Symbols (2011, methodology): “This does not always coincide with practice, where in many standard applications such as moving robots [Levesque and Lakemeyer, 2001], game playing agents and planners [Reiter, 2001], functions are either essential or in the least allow for succinct representations.”
A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents (2007, methodology): “2) Dynamical Systems Models: Dynamical systems theory has been used to complement classical approaches in artificial intelligence [91] and it has also been deployed to model natural and artificial cognitive systems [12], [13], [86].”
Multiagent Only Knowing in Dynamic Systems (2014, methodology): “To obtain the many features of OL in a dynamic setting, a logic ES (Lakemeyer & Levesque, 2011) was proposed that amalgamates OL and the situation calculus (McCarthy & Hayes, 1969; Reiter, 2001; Scherl & Levesque, 2003).”