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Pei Wang - A General Theory of Intelligence [an e-book under development] | Home
This eBook is an attempt to establish a theory that identifies the commonality within various forms intelligence, including human intelligence, computer intelligence, animal intelligence, alien intelligence, group intelligence, etc. -- NARS (Non-Axiomatic Reasoning System) - Most of the existing AI inference works with semi-axiomatic systems, which attempt to make partial extension or revision of mathematical logic, while keeping the other parts. What AI really needs are non-axiomatic systems, which do not assume the sufficiency of knowledge and resources in any aspect of the system. NARS is a concrete example of non-axiomatic system which uses a formal language "Narsese" to represent goals, actions, and beliefs.The basic unit of the language is term, which can be thought of as the name or label of a concept in the system. (..) The meaning of a term is determined by its extension and intension, which are the collection of the inheritance relations between this term and other terms, obtained from the experience of the system. NARS includes three variants of the inheritance relation: similarity (symmetric inheritance), implication (derivability), and equivalence (symmetric implication). (..)The meaning of a compound term is partially determined by its logical relations with its components, and partially by the system's experience on the compound term as a whole. Event is a special type of statement that have a time-dependent truth-value. Operation is a special type of event that can occur by the system's decision. Goal is a special type of event, that the system is attempting to realize, by carrying out certain operations. Beside goals to be achieved, NARS can accept tasks that are knowledge to be absorbed and questions to be answered. (..)If a event is judged to imply the achieving of a goal, then the desirability of the event is increased, and the system will also evaluate its plausibility(..). When an event is both desirable and plausible, the system will make the decision to turn the event into a goal to be actually pursued. The basic function of inference rules in NARS is to derive new beliefs from current beliefs.
etexts  books  intelligence  artificial_intelligence  mind  systems-complex_adaptive  systems-reflexive  systems_theory  epistemology-social  cognition  cognition-social  agent-based_models  logic  inference  decision_theory  rationality  rationality-bounded  learning  website  EF-add 
november 2014 by dunnettreader
Eric D. Beinhocker : Reflexivity, complexity, and the nature of social science - Journal of Economic Methodology [Soros special issue] - Volume 20, Issue 4 - Taylor & Francis Online
pages 330-342 -- downloaded pdf to Note -- In 1987, George Soros introduced his concepts of reflexivity and fallibility and has further developed and applied these concepts over subsequent decades. This paper attempts to build on Soros's framework, provide his concepts with a more precise definition, and put them in the context of recent thinking on complex adaptive systems. The paper proposes that systems can be classified along a ‘spectrum of complexity’ and that under specific conditions not only social systems but also natural and artificial systems can be considered ‘complex reflexive.’ The epistemological challenges associated with scientifically understanding a phenomenon stem not from whether its domain is social, natural, or artificial, but where it falls along this spectrum. Reflexive systems present particular challenges; however, evolutionary model-dependent realism provides a bridge between Soros and Popper and a potential path forward for economics.
article  philosophy_of_science  philosophy_of_social_science  epistemology  methodology  complexity  Soros  reflexivity  intentionality  evolution-as-model  Popper  scientific_method  downloaded  EF-add  systems-complex_adaptive  systems-reflexive  systems_theory  economic_theory  economic_models  EMH  rationality-economics  rational_expectations  information-markets  cognition  cognition-social  falsification  neuroscience  uncertainty  laws_of_nature  covering_laws  causation  explanation  prediction 
january 2014 by dunnettreader

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