Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints

In this paper, we present a new task that investigates how people interact with and make judgments about towers of blocks. In Experiment~1, participants in the lab solved a series of problems in which they had to re-configure three blocks from an initial to a final configuration. We recorded whether they used one hand or two hands to do so. In Experiment~2, we asked participants online to judge whether they think the person in the lab used one or two hands. The results revealed a close correspondence between participants' actions in the lab, and the mental simulations of participants online. To explain participants' actions and mental simulations, we develop a model that plans over a symbolic representation of the situation, executes the plan using a geometric solver, and checks the plan's feasibility by taking into account the physical constraints of the scene. Our model explains participants' actions and judgments to a high degree of quantitative accuracy

Understanding “almost”: Empirical and computational studies of near misses

When did something almost happen? In this paper, we in-vestigate what brings counterfactual worlds close. In Exper-iments 1 and 2, we find that participants’ judgments aboutwhether something almost happened are determined by thecausal proximity of the alternative outcome. Something almosthappened, when a small perturbation to the relevant causalevent would have been sufficient to bring it about. In contrastto previous work that has argued that prior expectations areneglected when judging the closeness of counterfactual worlds(Kahneman & Varey, 1990), we show in Experiment 3 thatparticipants are more likely to say something almost happenedwhen they did not expect it. Both prior expectations and causaldistance influence judgments of “almost”. In Experiment 4, weshow how both causal proximity and beliefs about what wouldhave happened in the absence of the cause jointly explain judg-ments of “almost caused” and “almost prevented”

Natural science: Active learning in dynamic physical microworlds

In this paper, we bring together research on active learningand intuitive physics to explore how people learn about“microworlds” with continuous spatiotemporal dynamics.Participants interacted with objects in simple two-dimensionalworlds governed by a physics simulator, with the goal ofidentifying latent physical properties such as mass, and forcesof attraction or repulsion. We find an advantage for activelearners over passive and yoked controls. Active participantsspontaneously performed several kinds of “natural exper-iments” which reveal the objects’ properties with varyingsuccess. While yoked participants’ judgments were affectedby the quality of the active participant they observed, they didnot share the learning advantage, performing no better thanpassive controls overall. We discuss possible explanations forthe divergence between active and yoked learners, and outlinefurther steps to categorize and explore active learning in thewild

Explaining intuitive difficulty judgments by modeling physical effort and risk

The ability to estimate task difficulty is critical for many real-world decisions such as setting appropriate goals for ourselves or appreciating others' accomplishments. Here we give a computational account of how humans judge the difficulty of a range of physical construction tasks (e.g., moving 10 loose blocks from their initial configuration to their target configuration, such as a vertical tower) by quantifying two key factors that influence construction difficulty: physical effort and physical risk. Physical effort captures the minimal work needed to transport all objects to their final positions, and is computed using a hybrid task-and-motion planner. Physical risk corresponds to stability of the structure, and is computed using noisy physics simulations to capture the costs for precision (e.g., attention, coordination, fine motor movements) required for success. We show that the full effort-risk model captures human estimates of difficulty and construction time better than either component alone

Concepts in a Probabilistic Language of Thought

Note: The book chapter is reprinted courtesy of The MIT Press, from the forthcoming edited collection “The Conceptual Mind: New Directions in the Study of Concepts” edited by Eric Margolis and Stephen Laurence, print date Spring 2015.Knowledge organizes our understanding of the world, determining what we expect given what we have already seen. Our predictive representations have two key properties: they are productive, and they are graded. Productive generalization is possible because our knowledge decomposes into concepts—elements of knowledge that are combined and recombined to describe particular situations. Gradedness is the observable effect of accounting for uncertainty—our knowledge encodes degrees of belief that lead to graded probabilistic predictions. To put this a different way, concepts form a combinatorial system that enables description of many different situations; each such situation specifies a distribution over what we expect to see in the world, given what we have seen. We may think of this system as a probabilistic language of thought (PLoT) in which representations are built from language-like composition of concepts and the content of those representations is a probability distribution on world states. The purpose of this chapter is to formalize these ideas in computational terms, to illustrate key properties of the PLoT approach with a concrete example, and to draw connections with other views of conceptual structure.This work was supported by ONR awards N00014-09-1-0124 and N00014-13- 1-0788, by a John S. McDonnell Foundation Scholar Award, and by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216

Antibiotic utilization in hospitalized children under 2 years of age with influenza or respiratory syncytial virus infection - a comparative, retrospective analysis

Background: Infections due to Respiratory Syncytial Virus (RSV) and Influenza virus (FLU) are leading causes of hospitalization in young children. Yet, there is little data on factors associated with antibiotic use in these patients. Methods: We conducted a retrospective, single-center study of all patients below 2 years of age hospitalized between 2014 and 2018. We compared children with RSV infection to children with FLU infection analyzing clinical characteristics and factors contributing to an increased rate of antimicrobial utilization. Results: RSV infection was diagnosed in 476/573 (83.1%), FLU in 95/573 (16.6%), and RSV-FLU-co-infection in 2/573 (0.3%) patients. Median age was lower for RSV compared to FLU (4 vs. 12 months; p < 0.0001). Children with RSV had longer hospitalization (5 vs. 4 days; p = 0.0023) and needed oxygen more frequently (314/476 vs. 23/95; p < 0.0001) than FLU patients. There was no significant difference in the overall antibiotic utilization between RSV and FLU patients (136/476 vs. 21/95; p = 0.2107). Logistic regression analyses revealed that septic appearance on admission (odds ratio [OR] 8.95, 95% confidence interval [CI] 1.5–54.1), acute otitis media (OR 4.5, 95% CI 2.1–9.4), a longer oxygen therapy (OR 1.40; 95% CI 1.13–1.74) and a higher C-reactive protein (CRP) (OR 1.7, 95% CI 1.5–2.0) were significantly associated with antibiotic use in both groups, but not age or pneumonia. Conclusions: In our cohort, the rate of antibiotic utilization was comparable between RSV and FLU patients, while for both groups distinct clinical presentation and a high CRP value were associated with higher antibiotic use

Go fishing! Responsibility judgments when cooperation breaks down

Many social judgments hinge on assigning responsibility to individuals for their role in a group’s success or failure. Often the group’s success depends on every team member acting in a rational way. When someone does not conform to what others expect of them, cooperation breaks down. We present a computational model of responsibility judgments for individuals in a cooperative setting. We test the model in two behavioral experiments where participants were asked to evaluate agents acting in a cooperative, one-shot game. In Experiment 1, we show that participants’ action predictions are consistent with a recursive reasoning model. In Experiment 2, we show that people’s assignments of blame are influenced by both an agent’s presumed rationality, or adherence to an expected policy, as well as the pivotality of the agent’s actions, or how close the situation was to one in which the action would have made a difference to the outcome

TNFα Induces Choroid Plexus Epithelial Cell Barrier Alterations by Apoptotic and Nonapoptotic Mechanisms

The choroid plexus epithelium constitutes the structural basis of the blood-cerebrospinal fluid barrier. Since the cytokine TNFα is markedly increased during inflammatory diseases in the blood and the central nervous system, we investigated by which mechanisms TNFα induces barrier alteration in porcine choroid plexus epithelial cells. We found a dose-dependent decrease of transepithelial electrical resistance, increase of paracellular inulin-flux, and induction of histone-associated DNA fragmentation and caspase-3 activation after TNFα stimulation. This response was strongly aggravated by the addition of cycloheximide and could partially be inhibited by the NF-κB inhibitor CAPE, but most effectively by the pan-caspase-inhibitor zVAD-fmk and not by the JNK inhibitor SP600125. Partial loss of cell viability could also be attenuated by CAPE. Immunostaining showed cell condensation and nuclear binding of high-mobility group box 1 protein as a sign of apoptosis after TNFα stimulation. Taken together our findings indicate that TNFα compromises PCPEC barrier function by caspase and NF-κB dependent mechanisms