Multiobjective Hierarchical Decision Problems in C3, IV.

1986 ◽  
Author(s):  
George P. Papavassilopoulos
Keyword(s):  
Decision Problems ◽  
Hierarchical Decision

scholarly journals Decision-Making in Flat and Hierarchical Decision Problems

2012 ◽  
Vol 4 (2) ◽  
pp. 23-36 ◽  
Author(s):  
Tadeusz Krupa ◽  
Teresa Ostrowska
Keyword(s):  
Decision Making ◽  
Decision Processes ◽  
Decision Problems ◽  
Hierarchical Decision ◽  
Decision Taking

Abstract The article is dedicated to the modelling of the essence of decision-taking processes in flat and hierarchical decision problems. In flat decision problems particular attention is drawn to the effectiveness of strategies in seeking decision variants on solution decomposition trees, taking into account the strength of their predefined contradictions. For hierarchical decision processes, the issue of iterative balancing of global (hierarchical) decisions is expressed, based on the valuation of the significance of flat decisions.

scholarly journals Dorsal anterior cingulate-midbrain ensemble as a reinforcement meta-learner

2017 ◽  
Author(s):  
Massimo Silvetti ◽  
Eliana Vassena ◽  
Elger Abrahamse ◽  
Tom Verguts
Keyword(s):  
Closed Loop ◽  
Instrumental Conditioning ◽  
Higher Order ◽  
Anterior Cingulate ◽  
Decision Problems ◽  
Behavioural Flexibility ◽  
Closed Loop System ◽  
Dorsal Anterior Cingulate Cortex ◽  
Internal Parameters ◽  
Hierarchical Decision

AbstractThe dorsal anterior cingulate cortex (dACC) is central in higher-order cognition and behavioural flexibility. The computational nature of this region, however, has remained elusive. Here we propose a new model – the Reinforcement Meta Learner (RML) – based on the bidirectional anatomical connections of the ACC with midbrain catecholamine nuclei (VTA and LC). In this circuit, dACC learns which actions are valuable and acts accordingly. Crucially, this mechanism is optimized by recurrent connectivity with the midbrain: Midbrain catecholamines provide modulatory signals to dACC, controlling its internal parameters (e.g. learning rate), while these parameter modulations are in turn optimized by dACC afferents to the midbrain. This closed-loop system generates emergent (i.e., homunculus-free) control and supports learning to solve hierarchical decision problems without having an intrinsic hierarchical structure itself. Further, it can be combined with other cortical modules to optimize the processing of these modules. We outline how the RML solves the current theoretical stalemate on dACC by assimilating various previous proposals on ACC functioning, and how it captures critical empirical findings from an unprecedented range of domains (stability/plasticity balance, effort processing, working memory, and higher-order classical and instrumental conditioning).

Wenn stadtpolitische Bewegungen das Terrain des Staats betreten

2018 ◽  
Vol 48 (191) ◽  
Author(s):  
Jonathan Diesselhorst
Keyword(s):  
Social Movements ◽  
City Government ◽  
Housing Policies ◽  
Hierarchical Decision Making ◽  
Urban Social Movements ◽  
State Apparatus ◽  
Hierarchical Decision ◽  
Relationship Of ◽  
The Relationship ◽  
The City

This article discusses the struggles of urban social movements for a de-neoliberalisation of housing policies in Poulantzian terms as a “condensation of the relationship of forces”. Drawing on an empirical analysis of the “Berliner Mietenvolksentscheid” (Berlin rent referendum), which was partially successful in forcing the city government of Berlin to adopt a more progressive housing policy, the article argues that urban social movements have the capacity to challenge neoliberal housing regimes. However, the specific materiality of the state apparatus and its strategic selectivity both limit the scope of intervention for social movements aiming at empowerment and non-hierarchical decision-making.

Bipolar Abstract Argumentation with Dual Attacks and Supports

2020 ◽  
Author(s):  
Nico Potyka
Keyword(s):  
Computational Complexity ◽  
Decision Problems ◽  
Abstract Argumentation ◽  
Stable Semantics ◽  
Support Relations ◽  
Support Relationships ◽  
Computational Properties ◽  
Inherent Tendency

Bipolar abstract argumentation frameworks allow modeling decision problems by defining pro and contra arguments and their relationships. In some popular bipolar frameworks, there is an inherent tendency to favor either attack or support relationships. However, for some applications, it seems sensible to treat attack and support equally. Roughly speaking, turning an attack edge into a support edge, should just invert its meaning. We look at a recently introduced bipolar argumentation semantics and two novel alternatives and discuss their semantical and computational properties. Interestingly, the two novel semantics correspond to stable semantics if no support relations are present and maintain the computational complexity of stable semantics in general bipolar frameworks.

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