Results 141 to 150 of about 816,456 (248)

Investigating Expertise in Probabilistic Reasoning

open access: yes
This study challenges traditional assumptions about human cognitive limitations in probabilistic reasoning by comparing performance between mathematical experts and novices on Bayesian reasoning tasks.
Matthew B Thompson   +2 more
core   +1 more source

Information Transmission Strategies for Self‐Organized Robotic Aggregation

open access: yesAdvanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng   +5 more
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

open access: yesAdvanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Bayesian teaching enables probabilistic reasoning in large language models. [PDF]

open access: yesNat Commun
Qiu L   +5 more
europepmc   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

open access: yesAdvanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek   +3 more
wiley   +1 more source

Probabilistic reasoning with answer sets

open access: yes, 2004
. We give a logic programming based account of probability and describe a declarative language P-log capable of reasoning which combines both logical and probabilistic arguments.
Chitta Baral   +2 more
core  

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