Matches in SemOpenAlex for { <https://semopenalex.org/work/W3091856707> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W3091856707 abstract "While reinforcement learning (RL) has been successful in natural language processing (NLP) domains such as dialogue generation and text-based games, it typically faces the problem of sparse rewards that leads to slow or no convergence. Traditional methods that use text descriptions to extract only a state representation ignore the feedback inherently present in them. In text-based games, for example, descriptions like Good Job! ate the food} indicate progress, and descriptions like You entered a new room indicate exploration. Positive and negative cues like these can be converted to rewards through sentiment analysis. This technique converts the sparse reward problem into a dense one, which is easier to solve. Furthermore, this can enable reinforcement learning without rewards, in which the agent learns entirely from these intrinsic sentiment rewards. This framework is similar to intrinsic motivation, where the environment does not necessarily provide the rewards, but the agent analyzes and realizes them by itself. We find that providing dense rewards in text-based games using sentiment analysis improves performance under some conditions." @default.
- W3091856707 created "2020-10-15" @default.
- W3091856707 creator A5041777363 @default.
- W3091856707 creator A5075793514 @default.
- W3091856707 date "2020-10-05" @default.
- W3091856707 modified "2023-09-27" @default.
- W3091856707 title "Sentiment Analysis for Reinforcement Learning." @default.
- W3091856707 cites W1777239053 @default.
- W3091856707 cites W2064675550 @default.
- W3091856707 cites W2101355568 @default.
- W3091856707 cites W2109462874 @default.
- W3091856707 cites W2113459411 @default.
- W3091856707 cites W2145339207 @default.
- W3091856707 cites W2201581102 @default.
- W3091856707 cites W2250432970 @default.
- W3091856707 cites W2257979135 @default.
- W3091856707 cites W2277684984 @default.
- W3091856707 cites W2549514639 @default.
- W3091856707 cites W2733961795 @default.
- W3091856707 cites W2739691807 @default.
- W3091856707 cites W2890809352 @default.
- W3091856707 cites W2917052767 @default.
- W3091856707 cites W2920768993 @default.
- W3091856707 cites W2950521938 @default.
- W3091856707 cites W2952222085 @default.
- W3091856707 cites W2954579883 @default.
- W3091856707 cites W2962957031 @default.
- W3091856707 cites W2963167310 @default.
- W3091856707 cites W2963341956 @default.
- W3091856707 cites W2964001908 @default.
- W3091856707 hasPublicationYear "2020" @default.
- W3091856707 type Work @default.
- W3091856707 sameAs 3091856707 @default.
- W3091856707 citedByCount "0" @default.
- W3091856707 crossrefType "posted-content" @default.
- W3091856707 hasAuthorship W3091856707A5041777363 @default.
- W3091856707 hasAuthorship W3091856707A5075793514 @default.
- W3091856707 hasConcept C119857082 @default.
- W3091856707 hasConcept C154945302 @default.
- W3091856707 hasConcept C15744967 @default.
- W3091856707 hasConcept C162324750 @default.
- W3091856707 hasConcept C17744445 @default.
- W3091856707 hasConcept C199539241 @default.
- W3091856707 hasConcept C204321447 @default.
- W3091856707 hasConcept C2776359362 @default.
- W3091856707 hasConcept C2777303404 @default.
- W3091856707 hasConcept C41008148 @default.
- W3091856707 hasConcept C50522688 @default.
- W3091856707 hasConcept C66402592 @default.
- W3091856707 hasConcept C67203356 @default.
- W3091856707 hasConcept C77805123 @default.
- W3091856707 hasConcept C94625758 @default.
- W3091856707 hasConcept C97541855 @default.
- W3091856707 hasConceptScore W3091856707C119857082 @default.
- W3091856707 hasConceptScore W3091856707C154945302 @default.
- W3091856707 hasConceptScore W3091856707C15744967 @default.
- W3091856707 hasConceptScore W3091856707C162324750 @default.
- W3091856707 hasConceptScore W3091856707C17744445 @default.
- W3091856707 hasConceptScore W3091856707C199539241 @default.
- W3091856707 hasConceptScore W3091856707C204321447 @default.
- W3091856707 hasConceptScore W3091856707C2776359362 @default.
- W3091856707 hasConceptScore W3091856707C2777303404 @default.
- W3091856707 hasConceptScore W3091856707C41008148 @default.
- W3091856707 hasConceptScore W3091856707C50522688 @default.
- W3091856707 hasConceptScore W3091856707C66402592 @default.
- W3091856707 hasConceptScore W3091856707C67203356 @default.
- W3091856707 hasConceptScore W3091856707C77805123 @default.
- W3091856707 hasConceptScore W3091856707C94625758 @default.
- W3091856707 hasConceptScore W3091856707C97541855 @default.
- W3091856707 hasLocation W30918567071 @default.
- W3091856707 hasOpenAccess W3091856707 @default.
- W3091856707 hasPrimaryLocation W30918567071 @default.
- W3091856707 hasRelatedWork W2551887912 @default.
- W3091856707 hasRelatedWork W2593766708 @default.
- W3091856707 hasRelatedWork W2751973545 @default.
- W3091856707 hasRelatedWork W2787329458 @default.
- W3091856707 hasRelatedWork W2790924949 @default.
- W3091856707 hasRelatedWork W2885550588 @default.
- W3091856707 hasRelatedWork W2900263002 @default.
- W3091856707 hasRelatedWork W2902567911 @default.
- W3091856707 hasRelatedWork W2963391602 @default.
- W3091856707 hasRelatedWork W2964294881 @default.
- W3091856707 hasRelatedWork W2980897231 @default.
- W3091856707 hasRelatedWork W2989640809 @default.
- W3091856707 hasRelatedWork W2998241503 @default.
- W3091856707 hasRelatedWork W3005607450 @default.
- W3091856707 hasRelatedWork W3016913676 @default.
- W3091856707 hasRelatedWork W3037425117 @default.
- W3091856707 hasRelatedWork W3091395917 @default.
- W3091856707 hasRelatedWork W3092995464 @default.
- W3091856707 hasRelatedWork W3156679053 @default.
- W3091856707 hasRelatedWork W3170843795 @default.
- W3091856707 isParatext "false" @default.
- W3091856707 isRetracted "false" @default.
- W3091856707 magId "3091856707" @default.
- W3091856707 workType "article" @default.