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This work proposes an object-oriented unified optimization framework (UOF) for general problem optimization.
The first is that users want "black box" software that they can use with complete confidence for general problem classes without having to understand the fine algorithmic details.
At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings.
In this paper, we argue that the study of these problems (examples of which include multi-agent interaction, instruction following and reasoning in complex domains) referred to under the rubric of Cognitive Robotics is best achieved via the use of cognitive architectures – unified computational frameworks developed specifically for general problem solving and human cognitive modeling.
A full-featured version of ePluribus for general problem solving will be developed in a Phase II program.
Our objectives for the ePluribus Solver fit into two complementary categories, the first addressing the challenges involved in forming a tool for general problem solving, the second addressing the challenges involved in soliciting and integrating large numbers of people in the problem solving process.
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Our results show that the present method is very accurate and that its implementation for general problems is straightforward.
Independent and completely confidential consultations also are available for general problems through the university ombudsperson, and for specific problems (e.g., sexual harassment, discrimination of any kind, psychological difficulties, health problems, etc).
We conclude the paper with a view of the design for a general problem solver that is a variant of the "big switch" theory of generality.
This set of weights is also the optimal one for the general problem, resulting in the fastest convergence of all possible SRJ schemes for a given grid structure.
We propose efficient heuristic algorithms for this general problem and evaluate them on various networks.
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CEO of Professional Science Editing for Scientists @ prosciediting.com