More obstacles on the road to unification

2007 ◽  
Vol 30 (1) ◽  
pp. 41-41 ◽  
Author(s):  
Eric Alden Smith
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Real World ◽  
Institutional Constraints ◽  
Historical Contingency ◽  
Behavioral Sciences ◽  
The Road ◽  
On The Road

The synthesis proposed by Gintis is valuable but insufficient. Greater consideration must be given to epistemological diversity within the behavioral sciences, to incorporating historical contingency and institutional constraints on decision-making, and to vigorously testing deductive models of human behavior in real-world contexts.

Game Theory-Based Framework for Modeling Human–Vehicle Interactions on the Road

2020 ◽  
Vol 2674 (9) ◽  
pp. 701-713
Author(s):  
Yalda Rahmati ◽  
Alireza Talebpour ◽  
Archak Mittal ◽  
James Fishelson
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Ground Truth ◽  
Realistic Model ◽  
Shared Environment ◽  
The Road ◽  
Interactive Behavior ◽  
Interactive Decision Making ◽  
Decision Making Framework ◽  
On The Road

New application domains have faded the barriers between humans and robots, introducing a new set of complexities to robotic systems. The major impediment is the uncertainties associated with human decision making, which makes it challenging to predict human behavior. A realistic model of human behavior is thus vital to capture humans’ interactive behavior with their surroundings and provide robots with reliable estimates on what is most likely to happen. Focusing on operations of connected and automated vehicles (CAVs) in areas with a high presence of human actors (i.e., pedestrians), this study creates an interactive decision-making framework to predict pedestrians’ trajectories when walking in a shared environment with vehicles and other pedestrians. It develops a game theoretical structure to approximate the movement and directional components of pedestrian motion using the theory of Nash equilibria in non-cooperative games. It also introduces a novel payoff structure to address the inherent uncertainties in human behavior. Ground truth pedestrian trajectories are then used to calibrate the game parameters and evaluate the model’s performance in approximating the motion decisions of human agents in interaction with interfering vehicles and pedestrians. The main contribution of the study is to develop an interactive human–vehicle decision-making framework toward realizing human–vehicle coexistence by capturing the effect of pedestrian–vehicle and pedestrian–pedestrian interactions on choice of walking strategies. The derived knowledge could be used in CAV navigation algorithms to provide the vehicle with more accurate predictions of pedestrian behavior, and in turn, improve CAV motion planning in human-populated areas.

scholarly journals On the Road to Holistic Decision Making in Adaptive Security

2013 ◽  
Vol 3 (8) ◽  
pp. 59-64 ◽  
Author(s):  
Mahsa Emami-Taba ◽  
Mehdi Amoui ◽  
Ladan Tahvildari
Keyword(s):  
Decision Making ◽  
Adaptive Security ◽  
The Road ◽  
On The Road

scholarly journals On the Road to Holistic Decision Making in Adaptive Security

2013 ◽  
Vol 3 (8) ◽  
pp. 59-64 ◽  
Author(s):  
Mahsa Emami-Taba ◽  
Mehdi Amoui ◽  
Ladan Tahvildari
Keyword(s):  
Decision Making ◽  
Adaptive Security ◽  
The Road ◽  
On The Road

scholarly journals A Coupled Model to Simulate Snow Behavior on Roads

2006 ◽  
Vol 45 (3) ◽  
pp. 500-516 ◽  
Author(s):  
Ludovic Bouilloud ◽  
Eric Martin
Keyword(s):  
Decision Making ◽  
Numerical Model ◽  
Good Accuracy ◽  
Coupled Model ◽  
Snow Layer ◽  
The Road ◽  
Snow Model ◽  
On The Road ◽  
Water Saturated ◽  
Decision Making Tool

Abstract To develop a decision-making tool for road management in winter, a numerical model resulting from the coupling of a soil model and a snow model was developed and validated using experimental results from a comprehensive experimental field campaign during three winters (1997/98, 1998/99, and 1999/2000). The coupling of the models has been done through an implicit calculation of the conduction flux between snow and road. An equivalent thermal resistance has been used to take into account the different road–snow interface configurations. For this purpose, a parameterization of water-saturated snow was introduced. This model permits the simulation of the snow behavior on a road, and it takes into account different interfacial configurations according to snow and road types and the snowpack evolution (freezing, melting, grain type). Comparisons of experimental and simulated results for typical snowfall events or over the entire winter showed that the model was able to simulate road surface temperature, snow occurrence on the road, and snow-layer evolution with good accuracy.

From skyhooks to walking sticks: On the road to nonrational decision making

1982 ◽  
Vol 11 (2) ◽  
pp. 40-58 ◽  
Author(s):  
Neil McK. Agnew ◽  
John L. Brown
Keyword(s):  
Decision Making ◽  
The Road ◽  
On The Road

To cross or not to cross: A closer look at children’s decision-making on the road

2021 ◽  
Vol 149 ◽  
pp. 1-11
Author(s):  
Kevin Y.K. Leung ◽  
Becky P.Y. Loo ◽  
K.L. Tsui ◽  
F.L. So ◽  
Ellen Fok
Keyword(s):  
Decision Making ◽  
The Road ◽  
On The Road

scholarly journals Geometry of neural computation unifies working memory and planning

2021 ◽  
Author(s):  
Daniel B. Ehrlich ◽  
John D. Murray
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Working Memory ◽  
Prefrontal Cortex ◽  
Human Behavior ◽  
Real World ◽  
Recurrent Neural Networks ◽  
Neural Computation ◽  
Neural Data ◽  
The Brain

Real-world tasks require coordination of working memory, decision making, and planning, yet these cognitive functions have disproportionately been studied as independent modular processes in the brain. Here we propose that contingency representations, defined as mappings for how future behaviors depend on upcoming events, can unify working memory and planning computations. We designed a task capable of disambiguating distinct types of representations. Our experiments revealed that human behavior is consistent with contingency representations, and not with traditional sensory models of working memory. In task-optimized recurrent neural networks we investigated possible circuit mechanisms for contingency representations and found that these representations can explain neurophysiological observations from prefrontal cortex during working memory tasks. Finally, we generated falsifiable predictions for neural data to identify contingency representations in neural data and to dissociate different models of working memory. Our findings characterize a neural representational strategy that can unify working memory, planning, and context-dependent decision making.

Sign in / Sign up

Export Citation Format

Share Document