Adaptive Reasoning for Real-world Problems

Turner, Roy M.

doi:10.4324/9780203773185

Cited by 8 publications

(15 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This realization led to a reasoning style called schema-based reasoning (SBR) [39] in which the generalized cases stored in MOPs are used as schemas to drive reasoning. Three kinds of schemas were identified: procedural schemas (p-schemas), contextual schemas (c-schemas), and strategic schemas (sschemas).…”

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

“…In the original work on the MEDIC medical diagnostic program (e.g., [36,39]) they represented generalized cases of diagnostic sessions and were called diagnostic MOPs (dxMOPs). As it became apparent that they were actually representing MEDIC being in a particular diagnostic context and were more general than just being diagnostic, they were renamed to reflect their role as general contextual knowledge structures.…”

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

“…While the ideas behind p-schemas and c-schemas continued to be pursued in later work on intelligent control of real-world physical systems (e.g., [46,39]) and on to the present work being discussed in this article, s-schemas were not pursued. As we discuss later, however, it may be that the notion of strategic knowledge needs to be resurrected, either as a separate kind of knowledge structure or as "meta-c-schemas" representing such things as "being an expert", "being a novice", and so forth.…”

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

“…ConMan can be an integrated part of an agent's reasoning process (e.g., in Orca [40,39]), or it can be an independent module that communicates with and provides contextual knowledge to the rest of the agent [43].…”

Section: Overall Cmb Processmentioning

confidence: 99%

“…This evolved into the approach to contextual reasoning called context-mediated behavior (CMB) [42], part of schema-based reasoning [39] and an off-shoot of case-based reasoning (e.g., [22]). …”

mentioning

confidence: 99%

See 4 more Smart Citations

Context-Mediated Behavior

Turner¹

2017

MUC

View full text Add to dashboard Cite

ABSTRACT. All effective agents are context-sensitive. This is true for biological agents, and it must also be true for artificial agents if they are to succeed. Context-mediated behavior (CMB) is one approach to endowing artificial agents with context-sensitive, context-appropriate behavior. It relies on explicitly representing contexts -important classes of situations -as contextual schemas and associating with them all the relevant knowledge about that context. The agent can then use these c-schemas to assess its context and their knowledge to behave appropriately. In this paper, we provide an overview of CMB, review the past work on it, discuss what we have learned from more than twenty years of working on the problem, and describe where we are and where we are going with CMB.

show abstract

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

Section: Origin Of Context-mediated Behaviormentioning

confidence: 99%

Section: Overall Cmb Processmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Context-Mediated Behavior

Turner¹

2017

MUC

View full text Add to dashboard Cite

show abstract

Pragmatic Research on Context Modeling and Use

Brézillon¹,

Turner²

2022

Modeling and Use of Context in Action

View full text Add to dashboard Cite

Pragmatic approaches to solving problems in artificial intelligence arise due to fast technological evolution as well as the complexity of real-world tasks. These operational, bottom-up approaches are based on representing how to behave in specific contexts. In this chapter, pragmatic approaches are discussed from the perspective of agents (human and AI) using data, information, and knowledge in context. Information is what is interpreted by an agent from data about the world, and what is exchanged with other agents. Information is highly context-dependent and under the control of the knowledge that is in the agent's "mind". Context plays a pivotal role in the development of information and knowledge. Setting data, information and knowledge in context allows new approaches to modeling (human and AI) reasoning. Based on its contextual knowledge (the part of its knowledge concerning the current focus), a reasoner interprets and uses information and produces new information and knowledge. Concretely, the pragmatic approach is shown in three examples of context-based research addressing applications in the real world. Operational knowledge in these approaches leads to contextualization of reasoning and opens the door to context-based AI systems.

show abstract

Adopting the sensemaking perspective for chronic disease self-management

Mamykina

Smaldone

Bakken

2015

Journal of Biomedical Informatics

119

108

View full text Add to dashboard Cite

Background Self-monitoring is an integral component of many chronic diseases; however few theoretical frameworks address how individuals understand self-monitoring data and use it to guide self-management. Purpose To articulate a theoretical framework of sensemaking in diabetes self-management that integrates existing scholarship with empirical data. Methods The proposed framework is grounded in theories of sensemaking adopted from organizational behavior, education, and human-computer interaction. To empirically validate the framework the researchers reviewed and analyzed reports on qualitative studies of diabetes self-management practices published in peer-reviewed journals from 2000 to 2015. Results The proposed framework distinguishes between sensemaking and habitual modes of self-management and identifies three essential sensemaking activities: perception of new information related to health and wellness, development of inferences that inform selection of actions, and carrying out daily activities in response to new information. The analysis of qualitative findings from 50 published reports provided ample empirical evidence for the proposed framework; however, it also identified a number of barriers to engaging in sensemaking in diabetes self-management. Conclusions The proposed framework suggests new directions for research in diabetes self-management and for design of new informatics interventions for data-driven self-management.

show abstract

Adaptive Reasoning for Real-world Problems

Cited by 8 publications

References 0 publications

Context-Mediated Behavior

Context-Mediated Behavior

Pragmatic Research on Context Modeling and Use

Adopting the sensemaking perspective for chronic disease self-management

Contact Info

Product

Resources

About