Matches in SemOpenAlex for { <https://semopenalex.org/work/W2902900917> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W2902900917 abstract "Researchers have established new techniques to study human-robot interactions based on current knowledge in interspecies communication and comparative psychology. Studies on animal acceptance of robot conspecifics in complex social environments has led to the development of robots that adapt to animal and human behaviors. Using a robot with adaptable algorithms developed by the authors, the researchers hypothesized that, by using familiar visual rewards as positive reinforcement, robots could use operant conditioning principles to teach humans a basic task. The robot in this study independently determines optimal control of construction equipment by capturing the motions from an expert operator. The robot then attempts to teach those same skills to novice operators using familiar, yet simple, visual reinforcement tools. In this study, participants were asked to manipulate a model excavator using feedback from the guidance system on a nearby computer screen. Participants were randomly assigned to one of three groups: simple visual reinforcement, complex guidance, and no visual feedback (blank screen). To measure learning, participants returned a day later to repeat the task without the guidance. The group using simple feedback resulted in cycle times that were closer to the expert times than both the complex or control groups and were significantly different end times (p < .05) than either group. This result supports our hypothesis that, similar to what’s been found in vertebrates and invertebrates, robots can shape behaviors of humans using visual positive reinforcement." @default.
- W2902900917 created "2018-12-11" @default.
- W2902900917 creator A5014357711 @default.
- W2902900917 creator A5063948391 @default.
- W2902900917 creator A5071263618 @default.
- W2902900917 creator A5073739058 @default.
- W2902900917 creator A5084822677 @default.
- W2902900917 date "2018-01-01" @default.
- W2902900917 modified "2023-09-29" @default.
- W2902900917 title "Robots Can Train Humans Using Principles of Operant Conditioning Through Visual Reinforcement Tools" @default.
- W2902900917 doi "https://doi.org/10.46867/ijcp.2018.31.04.01" @default.
- W2902900917 hasPublicationYear "2018" @default.
- W2902900917 type Work @default.
- W2902900917 sameAs 2902900917 @default.
- W2902900917 citedByCount "0" @default.
- W2902900917 crossrefType "journal-article" @default.
- W2902900917 hasAuthorship W2902900917A5014357711 @default.
- W2902900917 hasAuthorship W2902900917A5063948391 @default.
- W2902900917 hasAuthorship W2902900917A5071263618 @default.
- W2902900917 hasAuthorship W2902900917A5073739058 @default.
- W2902900917 hasAuthorship W2902900917A5084822677 @default.
- W2902900917 hasBestOaLocation W29029009171 @default.
- W2902900917 hasConcept C107457646 @default.
- W2902900917 hasConcept C127413603 @default.
- W2902900917 hasConcept C154945302 @default.
- W2902900917 hasConcept C15744967 @default.
- W2902900917 hasConcept C163270606 @default.
- W2902900917 hasConcept C180747234 @default.
- W2902900917 hasConcept C201995342 @default.
- W2902900917 hasConcept C2780451532 @default.
- W2902900917 hasConcept C41008148 @default.
- W2902900917 hasConcept C67203356 @default.
- W2902900917 hasConcept C77805123 @default.
- W2902900917 hasConcept C90509273 @default.
- W2902900917 hasConcept C97541855 @default.
- W2902900917 hasConceptScore W2902900917C107457646 @default.
- W2902900917 hasConceptScore W2902900917C127413603 @default.
- W2902900917 hasConceptScore W2902900917C154945302 @default.
- W2902900917 hasConceptScore W2902900917C15744967 @default.
- W2902900917 hasConceptScore W2902900917C163270606 @default.
- W2902900917 hasConceptScore W2902900917C180747234 @default.
- W2902900917 hasConceptScore W2902900917C201995342 @default.
- W2902900917 hasConceptScore W2902900917C2780451532 @default.
- W2902900917 hasConceptScore W2902900917C41008148 @default.
- W2902900917 hasConceptScore W2902900917C67203356 @default.
- W2902900917 hasConceptScore W2902900917C77805123 @default.
- W2902900917 hasConceptScore W2902900917C90509273 @default.
- W2902900917 hasConceptScore W2902900917C97541855 @default.
- W2902900917 hasLocation W29029009171 @default.
- W2902900917 hasOpenAccess W2902900917 @default.
- W2902900917 hasPrimaryLocation W29029009171 @default.
- W2902900917 hasRelatedWork W125126573 @default.
- W2902900917 hasRelatedWork W132120414 @default.
- W2902900917 hasRelatedWork W161290149 @default.
- W2902900917 hasRelatedWork W1980997780 @default.
- W2902900917 hasRelatedWork W2023938433 @default.
- W2902900917 hasRelatedWork W2164750759 @default.
- W2902900917 hasRelatedWork W2170999786 @default.
- W2902900917 hasRelatedWork W2214320789 @default.
- W2902900917 hasRelatedWork W2539976300 @default.
- W2902900917 hasRelatedWork W2557118676 @default.
- W2902900917 hasRelatedWork W2593604922 @default.
- W2902900917 hasRelatedWork W2620350838 @default.
- W2902900917 hasRelatedWork W2770513991 @default.
- W2902900917 hasRelatedWork W2899861365 @default.
- W2902900917 hasRelatedWork W2900299991 @default.
- W2902900917 hasRelatedWork W2904478167 @default.
- W2902900917 hasRelatedWork W2953778148 @default.
- W2902900917 hasRelatedWork W3112806953 @default.
- W2902900917 hasRelatedWork W3134584114 @default.
- W2902900917 hasRelatedWork W3134834355 @default.
- W2902900917 isParatext "false" @default.
- W2902900917 isRetracted "false" @default.
- W2902900917 magId "2902900917" @default.
- W2902900917 workType "article" @default.