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Automated planning and scheduling, sometimes denoted as simply AI planning, [1] is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
John Pollock's OSCAR system [2] is an example of an automated argumentation system that is more specific than being just an automated theorem prover. Tools and techniques of automated reasoning include the classical logics and calculi, fuzzy logic, Bayesian inference, reasoning with maximal entropy and many less formal ad hoc techniques.
Graphplan is an algorithm for automated planning developed by Avrim Blum and Merrick Furst in 1995. Graphplan takes as input a planning problem expressed in STRIPS and produces, if one is possible, a sequence of operations for reaching a goal state.
Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems (in particular, expert systems), symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems.
An algorithm that changes its behavior at the time it is run, based on a priori defined reward mechanism or criterion. adaptive neuro fuzzy inference system (ANFIS) Also adaptive network-based fuzzy inference system. A kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The technique was developed in the ...
An algorithm is a step-by-step procedure for calculations. Algorithms are used for calculation, data processing, and automated reasoning. An algorithm is an effective method expressed as a finite list [3] of well-defined instructions [4] for calculating a function. [5]
The inference engine uses general-purpose reasoning methods to infer new knowledge and to solve problems in the problem domain. Most commonly, it employs forward chaining or backward chaining . Other approaches include the use of automated theorem proving , logic programming , blackboard systems , and term rewriting systems such as Constraint ...
Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...