Partial Mental Simulation Explains Fallacies in Physical Reasoning

People can reason intuitively, efficiently, and accurately about everyday physical events. Recent accounts suggest that people use mental simulation to make such intuitive physical judgments. But mental simulation models are computationally expensive; how is physical reasoning relatively accurate, while maintaining computational tractability? We suggest that people make use of partial simulation, mentally moving forward in time only parts of the world deemed relevant. We propose a novel partial simulation model, and test it on the physical conjunction fallacy, a recently observed phenomenon (Ludwin-Peery, Bramley, Davis, & Gureckis, 2020) that poses a challenge for full simulation models. We find an excellent fit between our model's predictions and human performance on a set of scenarios that build on and extend those used by Ludwin-Peery et al. (2020), quantitatively and qualitatively accounting for a deviation from optimal performance. Our results suggest more generally how we allocate cognitive resources to efficiently represent and simulate physical scenes.

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Limits on the Use of Simulation in Physical Reasoning

10.31219/osf.io/mgbac ◽

2019 ◽

Author(s):

Ethan Ludwin-Peery ◽

Neil R Bramley ◽

Ernest Davis ◽

Todd Matthew Gureckis

Keyword(s):

Boundary Conditions ◽

Simulation Theory ◽

Conjunction Fallacy ◽

Mental Simulation ◽

Physical Reasoning ◽

Temporal Identity ◽

Spatio Temporal

In this paper, we describe three experiments involving simple physical judgments and predictions, and argue their results are generally inconsistent with three core commitments of probabilistic mental simulation theory (PMST). The first experiment shows that people routinely fail to track the spatio-temporal identity of objects. The second experiment shows that people often incorrectly reverse the order of consequential physical events when making physical predictions. Finally, we demonstrate a physical version of the conjunction fallacy where participants rate the probability of two joint events as more likely to occur than a constituent event of that set. These results highlight the limitations or boundary conditions of simulation theory.

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Limits on the Use of Simulation in Physical Reasoning

10.31234/osf.io/qbrvn ◽

2019 ◽

Cited By ~ 1

Author(s):

Ethan Ludwin-Peery ◽

Neil R Bramley ◽

Ernest Davis ◽

Todd Matthew Gureckis

Keyword(s):

Boundary Conditions ◽

Simulation Theory ◽

Conjunction Fallacy ◽

Mental Simulation ◽

Physical Reasoning ◽

Temporal Identity ◽

Spatio Temporal

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Broken Physics: A Conjunction-Fallacy Effect in Intuitive Physical Reasoning

Psychological Science ◽

10.1177/0956797620957610 ◽

2020 ◽

Vol 31 (12) ◽

pp. 1602-1611

Author(s):

Ethan Ludwin-Peery ◽

Neil R. Bramley ◽

Ernest Davis ◽

Todd M. Gureckis

Keyword(s):

Conjunction Fallacy ◽

Mental Simulation ◽

Human Cognition ◽

Single Event ◽

Physical Reasoning ◽

Conjunction Errors ◽

Intuitive Physics ◽

Logical Impossibility ◽

Rule Out

One remarkable aspect of human cognition is our ability to reason about physical events. This article provides novel evidence that intuitive physics is subject to a peculiar error, the classic conjunction fallacy, in which people rate the probability of a conjunction of two events as more likely than one constituent (a logical impossibility). Participants viewed videos of physical scenarios and judged the probability that either a single event or a conjunction of two events would occur. In Experiment 1 ( n = 60), participants consistently rated conjunction events as more likely than single events for the same scenes. Experiment 2 ( n = 180) extended these results to rule out several alternative explanations. Experiment 3 ( n = 100) generalized the finding to different scenes. This demonstration of conjunction errors contradicts claims that such errors should not appear in intuitive physics and presents a serious challenge to current theories of mental simulation in physical reasoning.

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Varieties of Understanding

10.1093/oso/9780190860974.001.0001 ◽

2019 ◽

Keyword(s):

Natural World ◽

Cognitive Resources ◽

The World ◽

Historical Tradition ◽

Normative Considerations ◽

Shed Light

According to a long historical tradition, understanding comes in different varieties. In particular, it is said that understanding people has a different epistemic profile than understanding the natural world—it calls on different cognitive resources, for instance, and brings to bear distinctive normative considerations. Thus in order to understand people we might need to appreciate, or in some way sympathetically reconstruct, the reasons that led a person to act in a certain way. By comparison, when it comes to understanding natural events, like earthquakes or eclipses, no appreciation of reasons or acts of sympathetic reconstruction is arguably needed—mainly because there are no reasons on the scene to even be appreciated, and no perspectives to be sympathetically pieced together. In this volume some of the world’s leading philosophers, psychologists, and theologians shed light on the various ways in which we understand the world, pushing debates on this issue to new levels of sophistication and insight.

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Guidelines to Calibrate a Multi-Residential Building Simulation Model Addressing Overheating Evaluation and Residents’ Influence

Buildings ◽

10.3390/buildings11060242 ◽

2021 ◽

Vol 11 (6) ◽

pp. 242

Author(s):

Christoph Schünemann ◽

David Schiela ◽

Regine Ortlepp

Keyword(s):

Simulation Model ◽

Time Window ◽

Residential Building ◽

Simulation Models ◽

Building Simulation ◽

Night Time ◽

Building Performance Simulation ◽

Starting Point ◽

3D Simulation Model ◽

Building Physics

Can building performance simulation reproduce measured summertime indoor conditions of a multi-residential building in good conformity? This question is answered by calibrating simulated to monitored room temperatures of several rooms of a multi-residential building for an entire summer in two process steps. First, we did a calibration for several days without the residents being present to validate the building physics of the 3D simulation model. Second, the simulations were calibrated for the entire summer period, including the residents’ impact on evolving room temperature and overheating. As a result, a high degree of conformity between simulation and measurement could be achieved for all monitored rooms. The credibility of our results was secured by a detailed sensitivity analysis under varying meteorological conditions, shading situations, and window ventilation or room use in the simulation model. For top floor dwellings, a high overheating intensity was evoked by a combination of insufficient use of night-time window ventilation and non-heat-adapted residential behavior in combination with high solar gains and low heat storage capacities. Finally, the overall findings were merged into a process guideline to describe how a step-by-step calibration of residential building simulation models can be done. This guideline is intended to be a starting point for future discussions about the validity of the simplified boundary conditions which are often used in present-day standard overheating assessment.

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Settings, Experimentation and Evaluation of the Simulation Models

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.309.366 ◽

2013 ◽

Vol 309 ◽

pp. 366-371 ◽

Cited By ~ 4

Author(s):

František Manlig ◽

Radek Havlik ◽

Alena Gottwaldova

Keyword(s):

Simulation Model ◽

New Technology ◽

Simulation Models ◽

Manufacturing Processes ◽

Customer Requirements ◽

Evaluation Functions ◽

Operational Management ◽

Minimum Number ◽

User Friendly ◽

Setting Parameters

This paper deals with research in computer simulation of manufacturing processes. The paper summarizes the procedures associated with developing the model, experimenting with and evaluating the model results. The key area is of experimentation with the simulation model and evaluation using indicators or multi-criteria functions. With regards to the experiment the crucial variables are the simulation model. The key ideas are to set the number of variables, depending on what a given simulation will be. For example, when introducing new technology into production, modify the type of warehouse, saving workers, thus economizing. The simulation models for the operational management uses simplified models, if possible, a minimum number of variables to obtain the result in shortest possible time. These models are more user friendly and the course will be conducted mostly in the background. An example of a criteria function is the number of parts produced or production time. Multi-criteria function has given us the opportunity to make better quality decisions. It is based on the composition of several parameters, including their weight to one end point. The type of evaluation functions, whether it is an indicator or criteria function is selected and based on customer requirements. In most cases it is recommended to use the multi-dimensional function. It gives us a more comprehensive view of the results from the model and facilitates decision-making. The result of this paper is a display of setting parameters for the experimentation on a sample model. Furthermore, the comparisons of results with a multi-criteria objective function and one-criterion indicator.

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Human Performance Modeling of Reduced Manning Concepts for Navy Ships

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129604001907 ◽

1996 ◽

Vol 40 (19) ◽

pp. 987-991 ◽

Cited By ~ 3

Author(s):

Rick D. Archer ◽

G.W. Lewis ◽

John Lockett

Keyword(s):

System Integration ◽

Human Performance ◽

Performance Modeling ◽

Assessment Tool ◽

Simulation Models ◽

Hierarchical Decomposition ◽

Army Research Laboratory ◽

Multiple Resources ◽

Bridge Models ◽

And Task

WinCrew is a human performance assessment tool developed by the Army Research Laboratory, Human Research and Engineering Directorate that implements the Wickens' Theory of Multiple Resources. WinCrew supports the hierarchical decomposition of missions into functions and tasks. As a demonstration of the capability of WinCrew, simulation models of the activities performed by bridge personnel on a Navy Guided Missile Destroyer DDG51 were developed. The scenarios were chosen to illustrate the potential of task network based human performance modeling to address reduced manning issues for naval ship operations. In order to fully exercise the functionality of WinCrew, four bridge models were developed. One scenario was modeled for four different manning, automation, and task allocation configurations. The scenario modeled was entry into San Diego Harbor. The major events for the bridge team were: bearing fixes, gyro error checks, turns, precision anchoring, and obstacle avoidance. Results of the effort demonstrated the utility of workload modeling for assessing human system integration alternatives for shipboard manning.

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A Method to Define the Best Weld Sequence Using a Limited Number of Welding Simulation Analysis

Volume 6B: Materials and Fabrication ◽

10.1115/pvp2015-45556 ◽

2015 ◽

Cited By ~ 1

Author(s):

Mahyar Asadi ◽

Ghazi Alsoruji

Keyword(s):

Simulation Model ◽

Surrogate Model ◽

Simulation Analysis ◽

Combinatorial Problem ◽

Fem Analysis ◽

Simulation Models ◽

Computational Time ◽

Optimal Sequence ◽

Welded Structure ◽

Welding Sequence

Weld sequence optimization, which is determining the best (and worst) welding sequence for welding work pieces, is a very common problem in welding design. The solution for such a combinatorial problem is limited by available resources. Although there are fast simulation models that support sequencing design, still it takes long because of many possible combinations, e.g. millions in a welded structure involving 10 passes. It is not feasible to choose the optimal sequence by evaluating all possible combinations, therefore this paper employs surrogate modeling that partially explores the design space and constructs an approximation model from some combinations of solutions of the expensive simulation model to mimic the behavior of the simulation model as closely as possible but at a much lower computational time and cost. This surrogate model, then, could be used to approximate the behavior of the other combinations and to find the best (and worst) sequence in terms of distortion. The technique is developed and tested on a simple panel structure with 4 weld passes, but essentially can be generalized to many weld passes. A comparison between the results of the surrogate model and the full transient FEM analysis all possible combinations shows the accuracy of the algorithm/model.

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Rotorcraft Lateral-Directional Oscillations: The Anatomy of a Nuisance Mode

Journal of the American Helicopter Society ◽

10.4050/jahs.66.042009 ◽

2021 ◽

Author(s):

Dheeraj Agarwal ◽

Linghai Lu ◽

Gareth D. Padfield ◽

Mark D. White ◽

Neil Cameron

Keyword(s):

Simulation Model ◽

Simulation Models ◽

Flight Test ◽

Flight Simulation ◽

Stability And Control ◽

Systems Research ◽

Control Derivatives ◽

Research Aircraft ◽

Level Of Understanding ◽

And Control

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.

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Modeling and analysis of the characteristics of SiC MOSFET

Journal of Physics Conference Series ◽

10.1088/1742-6596/2125/1/012051 ◽

2021 ◽

Vol 2125 (1) ◽

pp. 012051

Author(s):

Guoqing Qiu ◽

Kedi Jiang ◽

Shengyou Xu ◽

Xin Yang ◽

Wei Wang

Keyword(s):

Simulation Model ◽

Circuit Simulation ◽

Power Conversion ◽

Simulation Models ◽

Data Sheet ◽

Superior Performance ◽

Power Devices ◽

Matlab Simulink ◽

Modeling And Analysis ◽

Mathematical Processing

Abstract Although the superior performance of SiC MOSFET devices has beenvalidated by many studies, it is necessary to overcome many technical bottlenecks to make SiC MOSFET gradually replace Si-based power devices into the mainstream. In view of the current situation where the performance of SiC MOSFETs in power conversion devices cannot be evaluated well at this stage, it is necessary to carry out fine modeling of SiC MOSFETs and establish accurate simulation models. In this paper, the powerful mathematical processing capability and rich modules of Matlab/Simulink are used to build a SiC MOSFET model, and then the product data sheet is compared with the fitted data. The results show that the switching simulation waveforms are in general agreement with the data sheet waveforms, and the error is less than 7%. Verifing the accuracy of the model and reducing the difficulty of modeling, it provides a new idea for establishing the circuit simulation model of SiC MOSFET in Matlab/Simulink.

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