Apprentissage par renforcement verbal - Historique des versions

Pitpitt le 30 septembre 2024 à 21:37

2024-09-30T21:37:20Z

← Version précédente		Version du 30 septembre 2024 à 17:37
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	~~==en construction==~~

	== Définition ==		== Définition ==
	L'apprentissage par renforcement verbal est un type d''''[[apprentissage par renforcement]]''' qui donne un retour d'information verbale ou linguistique qui peut être à la fois plus nuancé et spécifique que les récompenses scalaires utilisées dans l'apprentissage par renforcement traditionnel. Ce type d'apprentissage est principalement utilisé pour renforcer les agents linguistiques ainsi que pour augmenter leur capacité.		L'apprentissage par renforcement verbal est un type d''''[[apprentissage par renforcement]]''' qui donne un retour d'information verbale ou linguistique qui peut être à la fois plus nuancé et spécifique que les récompenses scalaires utilisées dans l'apprentissage par renforcement traditionnel. Ce type d'apprentissage est principalement utilisé pour renforcer les agents linguistiques ainsi que pour augmenter leur capacité.
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	''Verbal reinforcement learning is a type of reinforcement learning that provides verbal or linguistic feedback that can be both more nuanced and specific than the scalar rewards used in traditional reinforcement learning. This type of learning is mainly used to reinforce linguistic agents and increase their capacity.''		''Verbal reinforcement learning is a type of reinforcement learning that provides verbal or linguistic feedback that can be both more nuanced and specific than the scalar rewards used in traditional reinforcement learning. This type of learning is mainly used to reinforce linguistic agents and increase their capacity.''


	== Source ==		== Source ==
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	[https://medium.com/@vikram40441/implementing-reflexion-language-agents-with-verbal-reinforcement-learning-e4cb300278b6 Source : Medium]		[https://medium.com/@vikram40441/implementing-reflexion-language-agents-with-verbal-reinforcement-learning-e4cb300278b6 Source : Medium]

			[[Catégorie:GRAND LEXIQUE FRANÇAIS]]

	[[Catégorie:~~publication~~]]

Pitpitt : Pitpitt a déplacé la page Verbal Reinforcement Learning vers Apprentissage par renforcement verbal

2024-09-30T21:36:28Z

Pitpitt a déplacé la page Verbal Reinforcement Learning vers Apprentissage par renforcement verbal

← Version précédente	Version du 30 septembre 2024 à 17:36
(Aucune différence)

Arianne le 30 septembre 2024 à 15:48

2024-09-30T15:48:48Z

← Version précédente		Version du 30 septembre 2024 à 11:48
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	== Définition ==		== Définition ==
	~~XXXXXXXXX~~		L'apprentissage par renforcement verbal est un type d''''[[apprentissage par renforcement]]''' qui donne un retour d'information verbale ou linguistique qui peut être à la fois plus nuancé et spécifique que les récompenses scalaires utilisées dans l'apprentissage par renforcement traditionnel. Ce type d'apprentissage est principalement utilisé pour renforcer les agents linguistiques ainsi que pour augmenter leur capacité.

	== Français ==		== Français ==
	''' ~~XXXXXXXXX~~ '''		''' apprentissage par renforcement verbal '''

	== Anglais ==		== Anglais ==
	''' ~~Verbal Reinforcement Learning~~'''		''' verbal reinforcement learning'''

	~~Large language models (LLMs) have been increasingly~~ used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challenging for these language agents to quickly and efficiently learn from trial-and-error as traditional reinforcement learning ~~methods require extensive training samples and expensive model fine-tuning~~. ~~We propose Reflexion, a novel framework~~ to reinforce ~~language agents not by updating weights, but instead through~~ linguistic ~~feedback. Concretely, Reflexion~~ agents ~~verbally reflect on task feedback signals, then maintain~~ their own reflective text in an episodic memory buffer to induce better decision-making in subsequent trials. Reflexion is flexible enough to incorporate various types (scalar values or free-form language) and sources (external or internally simulated) of feedback signals, and obtains significant improvements over a baseline agent across diverse tasks (sequential decision-making, coding, language reasoning). For example, Reflexion achieves a 91% pass@1 accuracy on the HumanEval coding benchmark, surpassing the previous state-of-the-art GPT-4 that achieves 80%. We also conduct ablation and analysis studies using different feedback signals, feedback incorporation methods, and agent types, and provide insights into how they affect performance.		''Verbal reinforcement learning is a type of reinforcement learning that provides verbal or linguistic feedback that can be both more nuanced and specific than the scalar rewards used in traditional reinforcement learning. This type of learning is mainly used to reinforce linguistic agents and increase their capacity.''


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	[https://arxiv.org/abs/2303.11366 Source : arxiv]		[https://arxiv.org/abs/2303.11366 Source : arxiv]

			[https://medium.com/@vikram40441/implementing-reflexion-language-agents-with-verbal-reinforcement-learning-e4cb300278b6 Source : Medium]


	[[Catégorie:~~vocabulary~~]]
			[[Catégorie:publication]]

Pitpitt : Page créée avec « ==en construction== == Définition == XXXXXXXXX == Français == ''' XXXXXXXXX ''' == Anglais == ''' Verbal Reinforcement Learning''' Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challenging for these language agents to quickly and efficiently learn from trial-and-error as traditional reinforcement learning methods require extensive tra... »

2024-03-28T20:57:20Z

Page créée avec « ==en construction== == Définition == XXXXXXXXX == Français == ''' XXXXXXXXX ''' == Anglais == ''' Verbal Reinforcement Learning''' Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challenging for these language agents to quickly and efficiently learn from trial-and-error as traditional reinforcement learning methods require extensive tra... »

Nouvelle page

==en construction==

== Définition ==
XXXXXXXXX

== Français ==
''' XXXXXXXXX '''

== Anglais ==
''' Verbal Reinforcement Learning'''

Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challenging for these language agents to quickly and efficiently learn from trial-and-error as traditional reinforcement learning methods require extensive training samples and expensive model fine-tuning. We propose Reflexion, a novel framework to reinforce language agents not by updating weights, but instead through linguistic feedback. Concretely, Reflexion agents verbally reflect on task feedback signals, then maintain their own reflective text in an episodic memory buffer to induce better decision-making in subsequent trials. Reflexion is flexible enough to incorporate various types (scalar values or free-form language) and sources (external or internally simulated) of feedback signals, and obtains significant improvements over a baseline agent across diverse tasks (sequential decision-making, coding, language reasoning). For example, Reflexion achieves a 91% pass@1 accuracy on the HumanEval coding benchmark, surpassing the previous state-of-the-art GPT-4 that achieves 80%. We also conduct ablation and analysis studies using different feedback signals, feedback incorporation methods, and agent types, and provide insights into how they affect performance.

== Source ==

[https://arxiv.org/abs/2303.11366 Source : arxiv]

[[Catégorie:vocabulary]]

Apprentissage par renforcement verbal - Historique des versions

Pitpitt le 30 septembre 2024 à 21:37

Pitpitt : Pitpitt a déplacé la page Verbal Reinforcement Learning vers Apprentissage par renforcement verbal

Arianne le 30 septembre 2024 à 15:48

Pitpitt : Pitpitt a déplacé la page Verbal Reinforcement Learning vers Apprentissage par renforcement verbal