AlfWorld - Revision history

BPeat at 13:35, 23 March 2024

2024-03-23T13:35:27Z

BPeat at 00:17, 9 September 2023

2023-09-09T00:17:21Z

BPeat at 01:25, 17 June 2023

2023-06-17T01:25:31Z

BPeat at 14:15, 20 May 2023

2023-05-20T14:15:41Z

BPeat at 13:45, 20 May 2023

2023-05-20T13:45:12Z

BPeat at 13:37, 20 May 2023

2023-05-20T13:37:30Z

BPeat: /* ALFRED */

2023-05-20T13:36:17Z

‎ALFRED

BPeat at 12:59, 20 May 2023

2023-05-20T12:59:51Z

BPeat at 12:55, 20 May 2023

2023-05-20T12:55:19Z

BPeat at 12:50, 20 May 2023

2023-05-20T12:50:07Z

@@ Line 16: / Line 16: @@
 * [[ALFRED]]  ... Action Learning From Realistic Environments and Directives
-* [[Assistants]] ... [[Personal Companions]] ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
+* [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
 * [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [[Embodied AI]]

@@ Line 17: / Line 17: @@
 * [[ALFRED]]  ... Action Learning From Realistic Environments and Directives
 * [[Assistants]] ... [[Personal Companions]] ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
-* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
+* [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [[Embodied AI]]

@@ Line 16: / Line 16: @@
 * [[ALFRED]]  ... Action Learning From Realistic Environments and Directives
-* [[Assistants]]  ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
+* [[Assistants]] ... [[Personal Companions]] ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
 * [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [[Embodied AI]]

@@ Line 15: / Line 15: @@
 * [https://github.com/alfworld/alfworld AlfWorld | GitHub]
-* [[ALFRED]]
+* [[ALFRED]]  ... Action Learning From Realistic Environments and Directives
 * [[Assistants]]  ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
 * [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]

@@ Line 14: / Line 14: @@
 * [https://arxiv.org/abs/2010.03768 AlfWorld: Aligning Text and Embodied Environments for Interactive Learning | M. Shridhar, X. Yuan, M. Côté, Y. Bisk, A. Trischler, M. Hausknecht - arXiv]
 * [https://github.com/alfworld/alfworld AlfWorld | GitHub]
-* [[Embodied AI]]
 * [[Assistants]]  ... [[Agents]]  ... [[Negotiation]] ... [[LangChain]]
 * [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
-<b>AlfWorld</b>: Aligning Text and Embodied Environments for Interactive Learning. a simulator that enables agents to learn abstract, text based policies in TextWorld (Côté et al., 2018) and then execute goals from the ALFRED benchmark (Shridhar et al., 2020) in a rich visual environment. ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions. In turn, as we demonstrate empirically, this fosters better agent generalization than training only in the visually grounded environment. BUTLER's simple, modular design factors the problem to allow researchers to focus on models for improving every piece of the pipeline (language understanding, planning, navigation, and visual scene understanding). The aligned environments allow agents to reason and learn high-level policies in an abstract space before solving embodied tasks through low-level actuation.
+<b>AlfWorld</b>: Aligning Text and [[Embodied AI]] Environments for Interactive Learning. a simulator that enables agents to learn abstract, text based policies in TextWorld (Côté et al., 2018) and then execute goals from the [[ALFRED]] benchmark (Shridhar et al., 2020) in a rich visual environment. ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions. In turn, as we demonstrate empirically, this fosters better agent generalization than training only in the visually grounded environment. BUTLER's simple, modular design factors the problem to allow researchers to focus on models for improving every piece of the pipeline (language understanding, planning, navigation, and visual scene understanding). The aligned environments allow agents to reason and learn high-level policies in an abstract space before solving embodied tasks through low-level actuation.
@@ Line 25: / Line 27: @@
 <youtube>Iu2S1wWJ2T4</youtube>

@@ Line 26: / Line 26: @@
 <youtube>Iu2S1wWJ2T4</youtube>
-= ALFRED =
+= [[ALFRED]] =
 ALFRED (Action Learning From Realistic Environments and Directives) is a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. It includes long, compositional tasks with non-reversible state changes to shrink the gap between research benchmarks and real-world applications
 <youtube>-YmHT2fSQDo</youtube>
 <youtube>1XoRLNmXffo</youtube>