MétaCan
Menu
Back to cohort
Record W2163293603 · doi:10.1109/icsmc.2009.5346292

Constrained rationality: Formal goals-reasoning approach to strategic decision & conflict analysis

2009· article· en· W2163293603 on OpenAlexaff
Majed Al-Shawa, Otman Basir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRationalityComputer scienceSet (abstract data type)Strategic thinkingManagement scienceProperty (philosophy)Value (mathematics)Knowledge managementStrategic planningArtificial intelligenceOperations researchMathematicsEconomicsMachine learningManagementPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

This paper proposes Constrained Rationality, a formal qualitative goals and constraints reasoning framework for single and multi agents to analyze and rationalize about strategic decisions/conflicts. The framework suggests bringing back the strategic decision making problem to its roots: reasoning about options/alternatives, not to satisfy a set of preferences, but rather to satisfy the explicitly stated strategic and conflicting goals an agent has, given the internal and external complex and conflicting realities/constraints the agent has. The paper analyzes the relations among goals and constraints, how value property labels for goals (such as their achievement or prevention levels) propagates through these relations, and proposes a set of propagation rules and an algorithm to calculate the final value labels for goals at any point of time. The paper also presents some preliminary experimental results on using the algorithm to reason about a business strategic decision making scenario.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.305
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicMulti-Agent Systems and NegotiationFrench-language works237,207