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The Laptop is Safe from the Rain 273 35.5.3 Fetching the Toy Inside the Upper Cupboard 273 35.6 An Integrative Approach to Planning 275 36 Adaptive, Integrative Inference Control 277 36.1 Introduction 277 36.2 High-Level Control Mechanisms 277 36.2.1 The Need for Adaptive Inference Contr
ledge and intuition regarding CogPrime. For example, beyond the ideas presented here, there is a body of work on the OpenCog wiki site, and then the OpenCog codebase itself. More extensive introductory remarks may be found in Preface of Part 1, including a brief history of the book and acknowledgements
sign. No doubt it will evolve in some respects as implementation progresses; one of the principles kept in mind during the design and development of OpenCog was modular- ity, enabling substantial modifications to particular parts of the framework to occur without requiring wholesale changes throughout th
of the neighborhood of partial plans, and to guide PLN's inferences regarding the success likelihood of partial plans. EFTA00624423 Chapter 36 Adaptive, Integrative Inference Control 36.1 Introduction The subtlest and most difficult aspect of logical inference is not the logical rule-set nor the m
N nodes are activated and exported to the OpenCog Atomspace • Recognition that a block is present is carried out, either by - PLN inference within OpenCog, drawing the conclusion that a block is present from the exported predicates, using ImplicationLinks comprising a working definition of a "block"
ning to bridge DeSTIN and PLN Ls intended to fit. This architecture is not yet fully implemented, but is a straightforward extension of the current OpenCog architecture for processing data from game worlds IGEA08], and is scheduled for implementation later in 2013 in the course of a funded project invo
each rule with probability proportional to a certain weight associated with each rule. Initially we can assign these weights EFTA00624428 282 36 Adaptive, Integrative Inference Control generically, by hand, separately for each application domain. Later on they should be chosen adaptively, based on in
igence (or any other kind of highly powerful general intelligence), the creation of novel ideas will be paramount. New idea creation takes place in OpenCog via a variety of methods - e.g. inside MOSES which creates new program trees, PLN which creates new logical relationships, ECAN which creates new a
Entities connected to both Adaptive and OpenCog

Marc Rich
PERSONDeSTIN
ORGANIZATIONCogPrime
ORGANIZATIONConceptNodes
ORGANIZATION
Marvin Minsky
PERSONMindAgents
PERSONPredicateNode
LOCATIONPredicateNodes
ORGANIZATION
Python
ORGANIZATIONthe Webmind AI Engine
ORGANIZATIONImplicationLinks
ORGANIZATIONTruthValues
ORGANIZATIONCombo
LOCATIONSchemallode
PERSONOccam
PERSON
SubsetLink
PERSONMachine Learning
PERSONInference Control
ORGANIZATIONInheritanceLinks
ORGANIZATIONSchemata
ORGANIZATION