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World Model. ARVIND KUMAR IIS2012016 MANVENDRA KUMAR IIS2012018. Introduction:. Estimation of the state of the world Internal representation of the world is called world model. The world model may include models of objects, events, classes, tasks, and agents.
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World Model ARVIND KUMAR IIS2012016 MANVENDRA KUMAR IIS2012018
Introduction: • Estimation of the state of the world • Internal representation of the world is called world model. • The world model may include models of objects, events, classes, tasks, and agents. • WM is a Models of portions of the environment, and a model of the intelligent system itself.
Function of WM • WM processes maintain a rich and dynamic database of knowledge about the world in the form of images, maps, entities, events, and relationships at every level. • WM processes use that knowledge to generate estimates and predictions that support perception, reasoning, and planning at every level.
Function of WM • The world model includes all of the knowledge that is distributed throughout all the nodes in the 4D/RCS architecture. • world model enables the intelligent system to analyze the past, plan for the future, and • perceive sensory information in the context of expectations. • WM also generate prediction for BG planning and SP recursive estimation. • WM detect the faults.
Function of WM • Constructs and maintains an internal representation of entities, events, relationships and situations. • It generates predictions, expectations, beliefs and estimate of the probable results of future actions. • World Model update is made continuously and in an automatic way.
WM Updation:- • World model is updated according to perception. • Model refresh function is used to update the world model. Ex- Model=MRF{M,P}, where M=(V,R,Y,B,B) And Updated Model is (V,T,R,Y,B,B).
Knowledge Database:- • The data structures and the information content that collectively form the intelligent system’s world model • Knowledge database of the world model contains the information of the environment(state of the world) that sense by the sensor. • Knowledge database continuously updated in the system.
Knowledge database have three parts:- • A long term memory containing symbolic and iconic representations of all the generic and specific objects, events, that are known to intelligent system. • A short term memory containing iconic and symbolic representations of geometric entities and events, that are subject to current attention.
An instantaneous dynamic representation consisting of current sensor signals and values of observed, estimated, and predicted attributes and state variables.