17 research outputs found
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Ask or Tell: Balancing questions and instructions in intuitive teaching
Teaching is an intuitive social activity that requires reason-ing about and influencing the mind of others. A good teacherforms a belief about the knowledge of their student, asks clar-ifying questions, and gives instructions or explanations to tryto induce a target concept in the studentâs mind. We proposePartially Observable Markov Decision Processes (POMDPs)as a model of intuitive human teaching. According to this ac-count, teachers make pedagogical decisions with uncertaintyabout the knowledge state of their student. In two behavioralexperiments, human participants were tasked with balancingassessments (asking questions) and instructions to help teach astudent to build a tower of colored blocks. Human behavior inthe task was compared to the performance of a computerizedteaching algorithm optimized to solve the equivalent POMDP.Our results show that humans favor asking questions and estab-lishing common ground during teaching even at an economiccost and increase question asking as uncertainty grows
25th annual computational neuroscience meeting: CNS-2016
The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong
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Modeling Intuitive Teaching as Sequential Decision Making Under Uncertainty
Informal teaching is a ubiquitous social behavior with a rich evolutionary history. We model teaching as the decisionmaking problem of planning a sequence of actions to convey information to a naive learner. We compare humans intuitiveteaching actions in a simple collaborative game to the optimal solution of a Partially Observable Markov Decision Process(POMDP). In a teaching POMDP, the current state is the latent, unobservable knowledge of the student and pedagogicalactions may yield changes in that knowledge or provide partial information about the students state. In our experiment,human teachers balance assessment and instruction while incorporating prior information about student knowledge. View-ing teaching as a POMDP suggests specific predictions for when different teaching actions (e.g., testing versus instruction)should be preferred under different conditions. Improving our understanding of the decision making strategies that underlieintuitive teaching has a range of implications from education to clinical rehabilitation
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Moment-to-moment decisions of when and how to help another person
Helping is a universal human behavior, and is a core aspect of a functioning society. However, the decision to provide help, and what type of help to provide, is a complex cognitive calculation that weights many costs and benefits simultaneously. In this paper, we explore how various costs influence the moment-to-moment decision to help in a simple video game. Participants were paired with another human participant and were asked to make repeated decisions that could benefit either themselves or their partner.
Several preregistered manipulations altered the cost each person paid for actions in the environment, the intrinsic resource capacity of individuals to perform the task, the visibility of the other player's score, and the affordances within the environment for helping. The results give novel insight into the cost-benefit analyses that people apply when providing help, and highlight the role of reciprocity in influencing helping decisions
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Rule discovery performance unchanged by incentives
Human behavior is modulated by financial incentives, but it is not well understood what types of behavior are immune to incentive and why. The cognitive processes underlying behavior appear to create restrictions on the effect an individual's motivation will have on their performance. We investigate a classic category learning task for which the effect of financial incentives is still unknown (Shepard, Hovland, & Jenkins, 1961). Across four renditions of a category learning experiment, we find no effect of incentive on performance. On a fifth experiment requiring category recognition but not learning, we find a large effect on response time and small effect on task performance. Humans appear to selectively apply more effort in valuable contexts, but the effort is disproportionate with the performance improvement. Taken together, the results suggest that performance in tasks which require novel inductive insights are relatively immune to financial incentive, while tasks that require rote perseverance of a fixed strategy are more malleable
Modeling Second-Language Learning from a Psychological Perspective
Psychological research on learning and memory has tended to emphasize small-scale laboratory studies. However, large datasets of people using educational software provide opportunities to explore these issues from a new perspective. In this paper we describe our approach to the Duolingo Second Language Acquisition Modeling (SLAM) competition which was run in early 2018. We used a well-known class of algorithms (gradient boosted decision trees), with features partially informed by theories from the psychological literature. After detailing our modeling approach and a number of supplementary simulations, we reflect on the degree to which psychological theory aided the model, and the potential for cognitive science and predictive modeling competitions to gain from each other
Modeling Second-Language Learning from a Psychological Perspective
Psychological research on learning and memory has tended to emphasize small-scale laboratory studies. However, large datasets of people using educational software provide opportunities to explore these issues from a new perspective. In this paper we describe our approach to the Duolingo Second Language Acquisition Modeling (SLAM) competition which was run in early 2018. We used a well-known class of algorithms (gradient boosted decision trees), with features partially informed by theories from the psychological literature. After detailing our modeling approach and a number of supplementary simulations, we reflect on the degree to which psychological theory aided the model, and the potential for cognitive science and predictive modeling competitions to gain from each other
Stimulus Pauses and Perturbations Differentially Delay or Promote the Segregation of Auditory Objects: Psychoacoustics and Modeling
Segregating distinct sound sources is fundamental for auditory perception, as in the cocktail party problem. In a process called the build-up of stream segregation, distinct sound sources that are perceptually integrated initially can be segregated into separate streams after several seconds. Previous research concluded that abrupt changes in the incoming sounds during build-upâfor example, a step change in location, loudness or timingâreset the percept to integrated. Following this reset, the multisecond build-up process begins again. Neurophysiological recordings in auditory cortex (A1) show fast (subsecond) adaptation, but unified mechanistic explanations for the bias toward integration, multisecond build-up and resets remain elusive. Combining psychoacoustics and modeling, we show that initial unadapted A1 responses bias integration, that the slowness of build-up arises naturally from competition downstream, and that recovery of adaptation can explain resets. An early bias toward integrated perceptual interpretations arising from primary cortical stages that encode low-level features and feed into competition downstream could also explain similar phenomena in vision. Further, we report a previously overlooked class of perturbations that promote segregation rather than integration. Our results challenge current understanding for perturbation effects on the emergence of sound source segregation, leading to a new hypothesis for differential processing downstream of A1. Transient perturbations can momentarily redirect A1 responses as input to downstream competition units that favor segregation