scholarly journals The Psychology of Causal Perception and Reasoning

2010 ◽  
Author(s):  
David Danks
Keyword(s):  
Causal Reasoning ◽  
Causal Structure ◽  
Psychological Research ◽  
Causal Learning ◽  
Causal Beliefs ◽  
Causal Knowledge ◽  
Causal Relations ◽  
Causal Perception ◽  
The World ◽  
Causal Cognition

Causal beliefs and reasoning are deeply embedded in many parts of our cognition. We are clearly ‘causal cognizers’, as we easily and automatically (try to) learn the causal structure of the world, use causal knowledge to make decisions and predictions, generate explanations using our beliefs about the causal structure of the world, and use causal knowledge in many other ways. Because causal cognition is so ubiquitous, psychological research into it is itself an enormous topic, and literally hundreds of people have devoted entire careers to the study of it. Causal cognition can be divided into two rough categories: causal learning and causal reasoning. The former encompasses the processes by which we learn about causal relations in the world at both the type and token levels; the latter refers to the ways in which we use those causal beliefs to make further inferences, decisions, predictions, and so on.

scholarly journals The Development of Causal Reasoning

2017 ◽  
Author(s):  
Paul Muentener ◽  
Elizabeth Bonawitz
Keyword(s):  
Young Children ◽  
Causal Reasoning ◽  
Causal Structure ◽  
Statistical Evidence ◽  
Causal Learning ◽  
Causal Relationships ◽  
Older Children ◽  
Very Young Children ◽  
The World

Research on the development of causal reasoning has broadly focused on accomplishing two goals: understanding the origins of causal reasoning, and examining how causal reasoning changes with development. This chapter reviews evidence and theory that aim to fulfill both of these objectives. In the first section, it focuses on the research that explores the possible precedents for recognizing causal events in the world, reviewing evidence for three distinct mechanisms in early causal reasoning: physical launching events, agents and their actions, and covariation information. The second portion of the chapter examines the question of how older children learn about specific causal relationships. It focuses on the role of patterns of statistical evidence in guiding learning about causal structure, suggesting that even very young children leverage strong inductive biases with patterns of data to inform their inferences about causal events, and discussing ways in which children’s spontaneous play supports causal learning.

Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World

2017 ◽  
Author(s):  
Patricia W. Cheng ◽  
Hongjing Lu
Keyword(s):  
Search Space ◽  
Causal Learning ◽  
Causal Mechanism ◽  
Intuitive Reasoning ◽  
Causal Relations ◽  
Causal Understanding ◽  
Domain Specific ◽  
Specific Description ◽  
The World

This chapter illustrates the representational nature of causal understanding of the world and examines its implications for causal learning. The vastness of the search space of causal relations, given the representational aspect of the problem, implies that powerful constraints are essential for arriving at adaptive causal relations. The chapter reviews (1) why causal invariance—the sameness of how a causal mechanism operates across contexts—is an essential constraint for causal learning in intuitive reasoning, (2) a psychological causal-learning theory that assumes causal invariance as a defeasible default, (3) some ways in which the computational role of causal invariance in causal learning can become obscured, and (4) the roles of causal invariance as a general aspiration, a default assumption, a criterion for hypothesis revision, and a domain-specific description. The chapter also reviews a puzzling discrepancy in the human and non-human causal and associative learning literatures and offers a potential explanation.

scholarly journals Origins of the concepts cause, cost, and goal in prereaching infants

2019 ◽  
Vol 116 (36) ◽  
pp. 17747-17752 ◽  
Author(s):  
Shari Liu ◽  
Neon B. Brooks ◽  
Elizabeth S. Spelke
Keyword(s):  
Causal Structure ◽  
The State ◽  
Causal Knowledge ◽  
Causal Inferences ◽  
Physical Constraints ◽  
The World ◽  
Action At A Distance ◽  
Basic Intuition

We investigated the origins and interrelations of causal knowledge and knowledge of agency in 3-month-old infants, who cannot yet effect changes in the world by reaching for, grasping, and picking up objects. Across 5 experiments, n = 152 prereaching infants viewed object-directed reaches that varied in efficiency (following the shortest physically possible path vs. a longer path), goal (lifting an object vs. causing a change in its state), and causal structure (action on contact vs. action at a distance and after a delay). Prereaching infants showed no strong looking preference between a person’s efficient and inefficient reaches when the person grasped and displaced an object. When the person reached for and caused a change in the state of the object on contact, however, infants looked longer when this action was inefficient than when it was efficient. Three-month-old infants also showed a key signature of adults’ and older infants’ causal inferences: This looking preference was abolished if a short spatial and temporal gap separated the action from its effect. The basic intuition that people are causal agents, who navigate around physical constraints to change the state of the world, may be one important foundation for infants’ ability to plan their own actions and learn from the acts of others.

scholarly journals Causal inference using deep-learning variable selection identifies and incorporates direct and indirect causalities in complex biological systems

2021 ◽  
Author(s):  
Zhenjiang Fan ◽  
Kate F Kernan ◽  
Panayiotis V Benos ◽  
Gregory F Cooper ◽  
Scott W Canna ◽  
...  
Keyword(s):  
Deep Learning ◽  
Variable Selection ◽  
Causal Inference ◽  
Causal Structure ◽  
Complex Diseases ◽  
Therapeutic Agents ◽  
Causal Learning ◽  
Biological Data ◽  
Causal Relations ◽  
Biological Variables

In complex diseases, causal structure learning across biological variables is critical to identify modifiable triggers or potential therapeutic agents. A limitation of existing causal learning methods is that they cannot identify indirect causal relations, those that would interact through latent mediating variables. We developed the first computational method that identifies both direct and indirect causalities, causal inference using deep-learning variable-selection (causalDeepVASE). To accurately identify indirect causalities and incorporate them with direct causalities, causalDeepVASE develops a deep neural network approach and extends a flexible causal inference method. In simulated and biological data of various contexts, causalDeepVASE outperforms existing methods in identifying expected or validated causal relations. Further, causalDeepVASE facilitates a systematic understanding of complex diseases. For example, causalDeepVASE uniquely identified a possible causal relation between IFNγ and creatinine suggested in a polymicrobial sepsis model. In future biomedical studies, causalDeepVASE can facilitate the identification of driver genes and therapeutic agents.

scholarly journals Origins of the concepts cause, cost, and goal in prereaching infants

2019 ◽  
Author(s):  
Shari Liu ◽  
Neon Blue Brooks ◽  
Elizabeth Spelke
Keyword(s):  
Causal Structure ◽  
The State ◽  
Causal Knowledge ◽  
Causal Inferences ◽  
Physical Constraints ◽  
The World ◽  
Action At A Distance ◽  
Basic Intuition

We investigated the origins and interrelations of causal knowledge and knowledge of agency in 3-month-old infants, who cannot yet effect changes in the world by reaching for, grasping, and picking up objects. Across 5 experiments, N=152 prereaching infants viewed object-directed reaches that varied in efficiency (following the shortest physically possible path vs. a longer path), goal (lifting an object vs. causing a change in its state), and causal structure (action on contact vs. action at a distance and after a delay). Prereaching infants showed no strong looking preference between a person’s efficient and inefficient reaches when the person grasped and displaced an object. When the person reached for and caused a change in the state of the object on contact, however, infants looked longer when this action was inefficient than when it was efficient. Three-month-old infants also showed a key signature of adults’ and older infants’ causal inferences: This looking preference was abolished if a short spatial and temporal gap separated the action from its effect. The basic intuition that people are causal agents, who navigate around physical constraints to change the state of the world, may be one important foundation for infants’ ability to plan their own actions and learn from the acts of others.

Causal Reasoning in Non-Human Animals

2017 ◽  
Author(s):  
Christian Schloegl ◽  
Julia Fischer
Keyword(s):  
Causal Reasoning ◽  
Animal Species ◽  
Causal Structure ◽  
Convincing Evidence ◽  
Causal Learning ◽  
Cognitive Evolution ◽  
Selective Pressures ◽  
Cognitive Studies

One goal of comparative cognitive studies is to achieve a better understanding of the selective pressures and constraints that play a role in cognitive evolution. This chapter focuses on the question of causal reasoning in animals, which has mainly been investigated in tool-using and large-brained species. Our survey reveals that numerous animal species appear to be sensitive to violations of causality and may even be tuned to attend to causally relevant features. This, in turn, may facilitate causal learning. The ability to draw logical conclusions and make causal deductions, however, seems to be restricted to few species and limited to (ecologically) relevant contexts. It seems warranted to reject the traditional associationist view that non-human animals lack any understanding of causality, but convincing evidence for human-like abilities is lacking. For instance, animals do not appear to understand the causal structure of interventions.

Rethinking Temporal Contiguity and the Judgement of Causality: Effects of Prior Knowledge, Experience, and Reinforcement Procedure

2003 ◽  
Vol 56 (5) ◽  
pp. 865-890 ◽  
Author(s):  
Marc J. Buehner ◽  
Jon May
Keyword(s):  
Causal Relation ◽  
Causal Learning ◽  
Temporal Contiguity ◽  
Learning Theories ◽  
Causal Induction ◽  
Causal Relations ◽  
Free Operant ◽  
The Impact ◽  
Causal Cognition ◽  
Reinforcement Procedure

Time plays a pivotal role in causal inference. Nonetheless most contemporary theories of causal induction do not address the implications of temporal contiguity and delay, with the exception of associative learning theory. Shanks, Pearson, and Dickinson (1989) and several replications (Reed, 1992, 1999) have demonstrated that people fail to identify causal relations if cause and effect are separated by more than two seconds. In line with an associationist perspective, these findings have been interpreted to indicate that temporal lags universally impair causal induction. This interpretation clashes with the richness of everyday causal cognition where people apparently can reason about causal relations involving considerable delays. We look at the implications of cause-effect delays from a computational perspective and predict that delays should generally hinder reasoning performance, but that this hindrance should be alleviated if reasoners have knowledge of the delay. Two experiments demonstrated that (1) the impact of delay on causal judgement depends on participants’ expectations about the timeframe of the causal relation, and (2) the free-operant procedures used in previous studies are ill-suited to study the direct influences of delay on causal induction, because they confound delay with weaker evidence for the relation in question. Implications for contemporary causal learning theories are discussed.

Institutional actors: Children’s emerging beliefs about the causal structure of social roles

2019 ◽  
Author(s):  
Alexander Noyes ◽  
Frank Keil ◽  
Yarrow Dunham
Keyword(s):  
Soccer Player ◽  
Social Roles ◽  
Social Role ◽  
Causal Structure ◽  
Executive Orders ◽  
The Social ◽  
The World ◽  
Children's Beliefs ◽  
Institutional Actors ◽  
The U.S

Institutions make new forms of acting possible: Signing executive orders, scoring goals, and officiating weddings are only possible because of the U.S. government, the rules of soccer, and the institution of marriage. Thus, when an individual occupies a particular social role (President, soccer player, and officiator) they acquire new ways of acting on the world. The present studies investigated children’s beliefs about institutional actions, and in particular whether children understand that individuals can only perform institutional actions when their community recognizes them as occupying the appropriate social role. Two studies (Study 1, N = 120 children, 4-11; Study 2, N = 90 children, 4-9) compared institutional actions to standard actions that do not depend on institutional recognition. In both studies, 4- to 5-year-old children believed all actions were possible regardless of whether an individual was recognized as occupying the social role. In contrast, 8- to 9-year-old children robustly distinguished between institutional and standard actions; they understood that institutional actions depend on collective recognition by a community.

scholarly journals Cyclic quantum causal models

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jonathan Barrett ◽  
Robin Lorenz ◽  
Ognyan Oreshkov
Keyword(s):  
Causal Reasoning ◽  
Causal Structure ◽  
Bell Inequalities ◽  
Quantum Correlations ◽  
Quantum Systems ◽  
Causal Models ◽  
Causal Order ◽  
Quantum Processes ◽  
Causal Explanations ◽  
Causal Structures

AbstractCausal reasoning is essential to science, yet quantum theory challenges it. Quantum correlations violating Bell inequalities defy satisfactory causal explanations within the framework of classical causal models. What is more, a theory encompassing quantum systems and gravity is expected to allow causally nonseparable processes featuring operations in indefinite causal order, defying that events be causally ordered at all. The first challenge has been addressed through the recent development of intrinsically quantum causal models, allowing causal explanations of quantum processes – provided they admit a definite causal order, i.e. have an acyclic causal structure. This work addresses causally nonseparable processes and offers a causal perspective on them through extending quantum causal models to cyclic causal structures. Among other applications of the approach, it is shown that all unitarily extendible bipartite processes are causally separable and that for unitary processes, causal nonseparability and cyclicity of their causal structure are equivalent.

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