Lie to Me: Deceit detection via online behavioral learning

2011 ◽  
Author(s):  
Nisha Bhaskaran ◽  
Ifeoma Nwogu ◽  
Mark G. Frank ◽  
Venu Govindaraju
Keyword(s):  
Behavioral Learning

scholarly journals Emergent Robotic Personality Traits via Agent-Based Simulation of Abstract Social Environments

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 103
Author(s):  
Casey C. Bennett
Keyword(s):  
Personality Traits ◽  
Human Robot Interaction ◽  
Social Environments ◽  
Agent Based Simulation ◽  
Theoretical Frameworks ◽  
Behavioral Learning ◽  
Agent Based ◽  
Current State ◽  
The Stability ◽  
Markovian Approach

This paper discusses the creation of an agent-based simulation model for interactive robotic faces, built based on data from physical human–robot interaction experiments, to explore hypotheses around how we might create emergent robotic personality traits, rather than pre-scripted ones based on programmatic rules. If an agent/robot can visually attend and behaviorally respond to social cues in its environment, and that environment varies, then idiosyncratic behavior that forms the basis of what we call a “personality” should theoretically be emergent. Here, we evaluate the stability of behavioral learning convergence in such social environments to test this idea. We conduct over 2000 separate simulations of an agent-based model in scaled-down, abstracted forms of the environment, each one representing an “experiment”, to see how different parameters interact to affect this process. Our findings suggest that there may be systematic dynamics in the learning patterns of an agent/robot in social environments, as well as significant interaction effects between the environmental setup and agent perceptual model. Furthermore, learning from deltas (Markovian approach) was more effective than only considering the current state space. We discuss the implications for HRI research, the design of interactive robotic faces, and the development of more robust theoretical frameworks of social interaction.

scholarly journals Teacher enthusiasm and students’ social-behavioral learning engagement: The mediating role of student enjoyment and boredom in Chinese EFL classes

2021 ◽  
pp. 136216882110145
Author(s):  
Jean-Marc Dewaele ◽  
Chengchen Li
Keyword(s):  
Second Language Acquisition ◽  
Qualitative Interviews ◽  
Future Research ◽  
Learning Engagement ◽  
Behavioral Learning ◽  
Mediating Role ◽  
English Classes ◽  
Teacher Enthusiasm ◽  
Instructed Second Language Acquisition ◽  
Complex Relationships

Teacher enthusiasm is attracting growing attention in educational and learner psychology research. There is evidence that teacher enthusiasm is contagious in class and positively affects student emotions. Their fundamental role in shaping student engagement has also been well documented. However, the links – between teacher enthusiasm and student emotions, and between student emotions and engagement – remain underexplored in instructed second language acquisition. The present study adopted a mixed-method approach to examine the complex relationships between perceived teacher enthusiasm, emotions (enjoyment and boredom), and social-behavioral learning engagement among 2,002 learners of English as a foreign language (EFL) from 11 universities in China. Quantitative analyses showed small to large correlations between perceived teacher enthusiasm, enjoyment, boredom, and social-behavioral learning engagement. In addition, student enjoyment and boredom were found to co-mediate the relationship between perceptions of teacher enthusiasm and student social-behavioral engagement in English classes. Qualitative interviews with nine students provided insights into the potential causes of the statistical patterns. Theoretical and pedagogical implications are discussed, followed by directions for future research.

Eyeblink conditioning contingent on hippocampal theta enhances hippocampal and medial prefrontal responses

2011 ◽  
Vol 105 (5) ◽  
pp. 2213-2224 ◽  
Author(s):  
Ryan D. Darling ◽  
Kanako Takatsuki ◽  
Amy L. Griffin ◽  
Stephen D. Berry
Keyword(s):  
Neural Activity ◽  
Theta Rhythm ◽  
Eyeblink Conditioning ◽  
Trace Conditioning ◽  
Distributed Network ◽  
Field Potentials ◽  
Trace Interval ◽  
Behavioral Learning ◽  
Paired Group ◽  
Hippocampal Theta

Trace eyeblink classical conditioning (tEBCC) can be accelerated by making training trials contingent on the naturally generated hippocampal 3- to 7-Hz theta rhythm. However, it is not well-understood how the presence (or absence) of theta affects stimulus-driven changes within the hippocampus and how it correlates with patterns of neural activity in other essential trace conditioning structures, such as the medial prefrontal cortex (mPFC). In the present study, a brain-computer interface delivered paired or unpaired conditioning trials to rabbits during the explicit presence (T+) or absence (T−) of theta, yielding significantly faster behavioral learning in the T+-paired group. The stimulus-elicited hippocampal unit responses were larger and more rhythmic in the T+-paired group. This facilitation of unit responses was complemented by differences in the hippocampal local field potentials (LFP), with the T+-paired group demonstrating more coherent stimulus-evoked theta than T−-paired animals and both unpaired groups. mPFC unit responses in the rapid learning T+-paired group displayed a clear inhibitory/excitatory sequential pattern of response to the tone that was not seen in any other group. Furthermore, sustained mPFC unit excitation continued through the trace interval in T+animals but not in T−animals. Thus theta-contingent training is accompanied by 1) acceleration in behavioral learning, 2) enhancement of the hippocampal unit and LFP responses, and 3) enhancement of mPFC unit responses. Together, these data provide evidence that pretrial hippocampal state is related to enhanced neural activity in critical structures of the distributed network supporting the acquisition of tEBCC.

Alcohol Related Birth Defects: Implications for Education

1982 ◽  
Vol 12 (2) ◽  
pp. 113-123 ◽  
Author(s):  
Michael Lamanna
Keyword(s):  
New York ◽  
Birth Defects ◽  
School Adjustment ◽  
New York State ◽  
Department Of Education ◽  
York State Department ◽  
Preventive Action ◽  
Fetal Alcohol ◽  
Behavioral Learning ◽  
Community Agencies

This article emerges from a larger study of preventive approaches for Alcohol Related Birth Defects (ARBD) prepared for the New York State Department of Education. The author contends that in addition to clearly identifiable Fetal Alcohol Syndrome children, there is a continuum of impairment to the offspring of drinking mothers that is dose related and produces serious behavioral/learning deficits. The continuum includes young people of normal intelligence who perform below expected levels and find school adjustment difficult. School and community agencies need to conduct studies to determine the nature and extent of impairment and the kind of interventive and preventive action that should be instituted. To that end, this article gives information on the background and nature of ARBD and some suggestions to guide development of programs.

scholarly journals Sequential neuromodulation of Hebbian plasticity offers mechanism for effective reward-based navigation

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Zuzanna Brzosko ◽  
Sara Zannone ◽  
Wolfram Schultz ◽  
Claudia Clopath ◽  
Ole Paulsen
Keyword(s):  
Time Window ◽  
Hippocampal Slices ◽  
Learning Rule ◽  
Spike Timing ◽  
Synaptic Potentiation ◽  
Behavioral Learning ◽  
Hebbian Plasticity ◽  
Subsequent Application ◽  
Behavioral States ◽  
Synaptic Learning

Spike timing-dependent plasticity (STDP) is under neuromodulatory control, which is correlated with distinct behavioral states. Previously, we reported that dopamine, a reward signal, broadens the time window for synaptic potentiation and modulates the outcome of hippocampal STDP even when applied after the plasticity induction protocol (Brzosko et al., 2015). Here, we demonstrate that sequential neuromodulation of STDP by acetylcholine and dopamine offers an efficacious model of reward-based navigation. Specifically, our experimental data in mouse hippocampal slices show that acetylcholine biases STDP toward synaptic depression, whilst subsequent application of dopamine converts this depression into potentiation. Incorporating this bidirectional neuromodulation-enabled correlational synaptic learning rule into a computational model yields effective navigation toward changing reward locations, as in natural foraging behavior. Thus, temporally sequenced neuromodulation of STDP enables associations to be made between actions and outcomes and also provides a possible mechanism for aligning the time scales of cellular and behavioral learning.

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