An Extended Behavior Network for a Game Agent: An Investigation of Action Selection Quality and Agent Performance in Unreal Tournament

2005 ◽  
pp. 287-296 ◽  
Author(s):  
Hugo da Silva Corrêa Pinto ◽  
Luis Otávio Alvares
Keyword(s):  
Action Selection ◽  
Behavior Network ◽  
Extended Behavior

Sistem Pendukung Keputusan SNMPTN Jalur Undangan Dengan Metode Electre

2018 ◽  
Vol 3 ◽  
pp. 14
Author(s):  
Lidia K Simanjuntak ◽  
Tessa Y M Sihite ◽  
Mesran Mesran ◽  
Nuning Kurniasih ◽  
Yuhandri Yuhandri
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Action Selection ◽  
Multi Criteria Decision Making ◽  
Prospective Students ◽  
College Entrance ◽  
Electre Method ◽  
Selection Of

All colleges each year organize the selection of new admissions. Acceptance of prospective students in universities as education providers is done by selecting prospective students based on achievement in school and college entrance selection. To select the best student candidates based on predetermined criteria, then use Multi-Criteria Decision Making (MCDM) or commonly called decision support system. One method in MCDM is the Elimination Et Choix Traduisant la Reality (ELECTRE). The ELECTRE method is the best method of action selection. The ELECTRE method to obtain the best alternative by eliminating alternative that do not fit the criteria and can be applied to the decision SNMPTN invitation path.

scholarly journals GOALIATH: a theory of goal-directed behavior

2021 ◽  
Author(s):  
Bernhard Hommel
Keyword(s):  
Driving Forces ◽  
Action Selection ◽  
Action Control ◽  
Event File ◽  
Impact Action ◽  
Intentional Actions ◽  
Operational Characteristics ◽  
Different Origins ◽  
High Degree ◽  
Goal Directed Behavior

AbstractCommonsense and theorizing about action control agree in assuming that human behavior is (mainly) driven by goals, but no mechanistic theory of what goals are, where they come from, and how they impact action selection is available. Here I develop such a theory that is based on the assumption that GOALs guide Intentional Actions THrough criteria (GOALIATH). The theory is intended to be minimalist and parsimonious with respect to its assumptions, as transparent and mechanistic as possible, and it is based on representational assumptions provided by the Theory of Event Coding (TEC). It holds that goal-directed behavior is guided by selection criteria that activate and create competition between event files that contain action-effect codes matching one or more of the criteria—a competition that eventually settles into a solution favoring the best-matching event file. The criteria are associated with various sources, including biological drives, acquired needs (e.g., of achievement, power, or affiliation), and short-term, sometimes arbitrary, instructed aims. Action selection is, thus, a compromise that tries to satisfy various criteria related to different driving forces, which are also likely to vary in strength over time. Hence, what looks like goal-directed action emerges from, and represents an attempt to satisfy multiple constraints with different origins, purposes, operational characteristics, and timescales—which among other things does not guarantee a high degree of coherence or rationality of the eventual outcome. GOALIATH calls for a radical break with conventional theorizing about the control of goal-directed behavior, as it among other things questions existing cognitive-control theories and dual-route models of action control.

scholarly journals Constrained action selection in children with developmental coordination disorder

2008 ◽  
Vol 27 (2) ◽  
pp. 286-295 ◽  
Author(s):  
Lewis Pettit ◽  
Jennifer Charles ◽  
Andrew D. Wilson ◽  
Mandy S. Plumb ◽  
Anne Brockman ◽  
...  
Keyword(s):  
Developmental Coordination Disorder ◽  
Action Selection ◽  
Coordination Disorder

Effects of accelerator type on stress relaxation behavior and network structure of aged natural rubber/chloroprene rubber vulcanizates

2016 ◽  
Vol 49 (5) ◽  
pp. 381-396 ◽  
Author(s):  
Farzad A Nobari Azar ◽  
Murat Şen
Keyword(s):  
Stress Relaxation ◽  
Natural Rubber ◽  
Network Structure ◽  
Structural Changes ◽  
Relaxation Behavior ◽  
Stress Relaxation Behavior ◽  
Rubber Blends ◽  
Chloroprene Rubber ◽  
Weather Changes ◽  
Behavior Network

Natural rubber/chloroprene rubber (NR/CR) blends are among the commonly used rubber blends in industry and continuously are exposed to severe weather changes. To investigate the effects of accelerator type on the network structure and stress relaxation of unaged and aged NR/CE vulcanizates, tetramethyl thiuram disulfide, 2-mercaptobenzothiazole, and diphenyl guanidine accelerators have been chosen to represent fast, moderate, and slow accelerator groups, respectively. Three batches have been prepared with exactly the same components and mixing conditions differing only in accelerator type. Temperatures scanning stress relaxation and pulse nuclear magnetic resonance techniques have been used to reveal the structural changes of differently accelerated rubber blends before and after weathering. Nonoxidative thermal decomposition analyses have been carried out using a thermogravimetric analyzer. Results indicate that there is a strong interdependence between accelerator type and stress relaxation behavior, network structure, cross-linking density, and aging behavior of the blends. Accelerator type also affects decomposition energy of the blends.

scholarly journals γ-Aminobutyric acid (GABA) administration improves action selection processes: a randomised controlled trial

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Laura Steenbergen ◽  
Roberta Sellaro ◽  
Ann-Kathrin Stock ◽  
Christian Beste ◽  
Lorenza S. Colzato
Keyword(s):  
Randomised Controlled Trial ◽  
Controlled Trial ◽  
Action Selection ◽  
Aminobutyric Acid ◽  
Selection Processes ◽  
Randomised Controlled

scholarly journals Visual Information Shapes the Dynamics of Corticobasal Ganglia Pathways during Response Selection and Inhibition

2015 ◽  
Vol 27 (7) ◽  
pp. 1344-1359 ◽  
Author(s):  
Sara Jahfari ◽  
Lourens Waldorp ◽  
K. Richard Ridderinkhof ◽  
H. Steven Scholte
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Response Selection ◽  
Selection Process ◽  
Effective Connectivity ◽  
Action Selection ◽  
Visual Input ◽  
Fmri Data ◽  
Response Strategies ◽  
Fast Flow

Action selection often requires the transformation of visual information into motor plans. Preventing premature responses may entail the suppression of visual input and/or of prepared muscle activity. This study examined how the quality of visual information affects frontobasal ganglia (BG) routes associated with response selection and inhibition. Human fMRI data were collected from a stop task with visually degraded or intact face stimuli. During go trials, degraded spatial frequency information reduced the speed of information accumulation and response cautiousness. Effective connectivity analysis of the fMRI data showed action selection to emerge through the classic direct and indirect BG pathways, with inputs deriving form both prefrontal and visual regions. When stimuli were degraded, visual and prefrontal regions processing the stimulus information increased connectivity strengths toward BG, whereas regions evaluating visual scene content or response strategies reduced connectivity toward BG. Response inhibition during stop trials recruited the indirect and hyperdirect BG pathways, with input from visual and prefrontal regions. Importantly, when stimuli were nondegraded and processed fast, the optimal stop model contained additional connections from prefrontal to visual cortex. Individual differences analysis revealed that stronger prefrontal-to-visual connectivity covaried with faster inhibition times. Therefore, prefrontal-to-visual cortex connections appear to suppress the fast flow of visual input for the go task, such that the inhibition process can finish before the selection process. These results indicate response selection and inhibition within the BG to emerge through the interplay of top–down adjustments from prefrontal and bottom–up input from sensory cortex.

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