A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
Adaptive Procedural Task Generation for Hard-Exploration Problems
[article]
2021
arXiv
pre-print
Preserved Fulltext
Other Versions
We introduce Adaptive Procedural Task Generation (APT-Gen), an approach to progressively generate a sequence of tasks as curricula to facilitate reinforcement learning in hard-exploration problems. ...
At the heart of our approach, a task generator learns to create tasks from a parameterized task space via a black-box procedural generation module. ...
We would like to thank Roberto Martín-Martín, Austin Narcomey, Sriram Somasundaram, Fei Xia, and Danfei Xu for feedback on an early draft of the paper. ...
arXiv:2007.00350v3
fatcat:325qus6ovjhonf2fheip6sahei
Automatic Curriculum Learning For Deep RL: A Short Survey
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In recent years, they have been used to improve sample efficiency and asymptotic performance, to organize exploration, to encourage generalization or to solve sparse reward problems, among others. ...
adapted to their capacities. ...
A more general -and arguably more powerful-approach is to leverage parametric Procedural Content Genera-tion (PCG) techniques [Risi and Togelius, 2019] to generate rich task spaces. ...
arXiv:2003.04664v2
fatcat:lhire3htmnenfetx2ry4furgyy
Learning Not to Learn: Nature versus Nurture in Silico
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Further analysis reveals that non-adaptive behaviors are not only optimal for aspects of the environment that are stable across individuals, but also in situations where an adaptation to the environment ...
'hard-coded' behavior. ...
Acknowledgments We thank Nir Moneta for many initial discussions. ...
arXiv:2010.04466v3
fatcat:eo5gmen7zfbxhaao6gz563rbhi
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2020 pre-print arXiv:2009.13891v2 fatcat:h25ovhflqnffpl5cw45duwnl2eOther Versions
By conditioning on an effective context, Meta-RL policies can easily generalize to new tasks within a few adaptation steps. ...
Context, the embedding of previous collected trajectories, is a powerful construct for Meta-Reinforcement Learning (Meta-RL) algorithms. ...
Acknowledgements We thank Chenjia Bai, Qianli Shen, and Weixun Wang for useful discussions and suggestions. ...
arXiv:2009.13891v3
fatcat:6mpsw4qkuzgcpfv2hgtcskyze4
Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The core of SGA is to calculate "hardness" factors for sample pairs indicating domain distance in a kernel space. ...
Indicated by hardness factors, Self-Guided Progressive Sampling (SPS) is implemented in an "easy-to-hard" way during model adaptation. ...
Model Analysis For further exploring the effectiveness of proposed approaches, we analyze both training procedures and detection results from following aspects, which are performed over tasks: Pascal VOC ...
arXiv:2003.08777v2
fatcat:6xj52frxqrerrnx2lmtzh7cm2i
Hybridized TABU-BFO Algorithmin Grid Scheduling
2013
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Tabu search is a heuristic procedure which uses its adaptive memory structures in order to find optimal solution in grid scheduling. ...
Task Scheduling is an important issue in Grid Environment of multiprocessors system. The problem of scheduling a set of dependent and independent Task in a distributed system is considered. ...
One of the main issue in task Scheduling is the NP-Hard problem. Thus to avoid such a problem in the grid environment Tabu search concept is introduced. ...
doi:10.5120/10514-5484
fatcat:4ike5w67m5b6pdrn6k47ak66yy
PARSSSE: AN ADAPTIVE PARALLEL STATE SPACE SEARCH ENGINE
2011
Parallel Processing Letters
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Solving such problems is generally NP-hard, so that a brute-force approach to state space search must be employed. ...
Moreover, we tackle the problem of programmer productivity by incorporating these techniques into a general search engine framework designed to solve a broad class of state space search problems. ...
Acknowledgments This work was supported in part by NSF grant OCI-0725070 for Blue Waters deployment and NSF grant ITR-HECURA-0833188, by the Institute for Advanced Computing Applications and Technologies ...
doi:10.1142/s0129626411000242
fatcat:nqdtfz46qzal5mv3kxpzypirui
A Review of Methodologies for Natural-Language-Facilitated Human-Robot Cooperation
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this review, a comprehensive summary about methodologies for NLC is presented. ...
NLC research includes three main research focuses: NL instruction understanding, NL-based execution plan generation, and knowledge-world mapping. ...
Typical tackled problems include using MLN to generate a flexible machine-executable plan from human NL instructions for autonomous industrial task execution [28] , NL-based cooperation in uncertain environments ...
arXiv:1701.08756v3
fatcat:gquzgq3w6bcf5ih4aubchyyulm
Automated Curriculum Learning for Turn-level Spoken Language Understanding with Weak Supervision
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Furthermore, considering the diversity of problem complexity, we explore automated curriculum learning (CL) for weak supervision to accelerate exploration and learning. ...
We employ randomized beam search with memory augmentation (RBSMA) to solve complicated problems for which long promising trajectories are usually difficult to explore. ...
We propose two techniques for better exploration and generalization: (1) RBSMA for complicated problems with long programs, (2) automated CL for weakly supervised learning for dealing with the diversity ...
arXiv:1906.04291v1
fatcat:jro2hpn2gjatrlimyqcwv7xlne
Self-explanatory user interfaces by model-driven engineering
2010
Proceedings of the 2nd ACM SIGCHI symposium on Engineering interactive computing systems - EICS '10
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We explore modeldriven engineering to understand why and how this approach can lead us to overcome shortcomings of UI quality successfully. ...
Modern User Interfaces (UI) must deal with the increasing complexity of applications as well as new features such as the capacity of UIs to be dynamically adapted to the context of use. ...
Even many long-time users never master common procedures [6] and in other cases, users must work hard to figure out each feature or screen [6] . The problem is greater for Plastic UIs [5, 19] . ...
doi:10.1145/1822018.1822076
dblp:conf/eics/Frey10
fatcat:olfwqledm5arfewwchqov2pjsm
DAWSON: A Domain Adaptive Few Shot Generation Framework
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To this end, we propose DAWSON, a Domain Adaptive FewShot Generation FrameworkFor GANs based on meta-learning. ...
Training a Generative Adversarial Networks (GAN) for a new domain from scratch requires an enormous amount of training data and days of training time. ...
Acknowledgement This work was done as a course project for CS 236 Deep Generative Models at Stanford University. ...
arXiv:2001.00576v1
fatcat:wjud4apyubdlzohgmiaw5qb4mm
Collective Decision Making under Incomplete Knowledge: Possible and Necessary Solutions
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Most solution concepts in collective decision making are defined assuming complete knowledge of individuals' preferences and of the mechanism used for aggregating them. ...
A more general -and arguably more powerful-approach is to leverage parametric Procedural Content Generation (PCG) techniques [Risi and Togelius, 2019] to generate rich task spaces. ...
ACL mechanisms are used with a particular goal in mind (e.g. organizing exploration, solving hard tasks, etc. § 3). It controls a particular element of task MDPs (e.g. ...
doi:10.24963/ijcai.2020/671
dblp:conf/ijcai/PortelasCWHO20
fatcat:nqkxitg6yzbzvor2c3bi6rib5q
A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems
2019
The Journal of Artificial Intelligence Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We define a taxonomy of solutions for the general knowledge reuse problem, providing a comprehensive discussion of recent progress on knowledge reuse in Multiagent Systems (MAS) and of techniques for knowledge ...
Multiagent Reinforcement Learning (RL) solves complex tasks that require coordination with other agents through autonomous exploration of the environment. ...
Taylor for the collaboration in previous versions of this survey. ...
doi:10.1613/jair.1.11396
fatcat:mn4gw6oh5zgszl6l53fgesei5i
A Brief Look at Generalization in Visual Meta-Reinforcement Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we assess the generalization performance of these algorithms by leveraging high-dimensional, procedurally generated environments. ...
We also observe that scalability to high-dimensional tasks with sparse rewards remains a significant problem among many of the current meta-reinforcement learning algorithms. ...
These works use procedural content generation to evaluate generalization in regular RL algorithms. ...
arXiv:2006.07262v3
fatcat:7zkmbze76vb7rjl4vd4judrqyu
A new approach to comparing problem solving, flexibility and innovation
2012
Communicative & Integrative Biology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
One major reason for this is that it is very hard to find universally applicable paradigms that can be used to investigate the same cognitive ability or 'general intelligence' in several species. ...
Potentially revealing profiles could be obtained from examining species differences in how novel experimental (extractive foraging) tasks are explored and approached, how solutions are discovered and which ...
It highlights how different performance in problem solving task are not always symptomatic of species differences in cognitive ability or general intelligence. ...
doi:10.4161/cib.18787
pmid:22808317
pmcid:PMC3376048
fatcat:2ffmgrevfjd37akaxdqy5hwpmu
« Previous
Showing results 1 — 15 out of 241,717 results