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Jan 19th 2021
News
Amii welcomes 15 additional Canada CIFAR AI Chairs
As part of the January 2021 AICan, Amii is pleased to welcome 15 new Canada CIFAR AI Chairs into our research community.
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Dec 20th 2020
Research Post
Looking Back on the Actor-Critic Architecture
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Nov 30th 2020
News
Amii accepted papers, workshops & tutorials at NeurIPS 2020
Amii is proud to share the efforts and achievements of our researchers at the 34th Conference on Neural Information Processing Systems (NeurIPS), running online this year Dec 6 - 12.
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Nov 9th 2020
Research Post
From Eye-blinks to State Construction: Diagnostic Benchmarks for Online Representation Learning
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Oct 28th 2020
Research Post
Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning
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Sep 28th 2020
Research Post
Incremental Policy Gradients for Online Reinforcement Learning Control
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Aug 27th 2020
Research Post
Document-editing Assistants and Model-based Reinforcement Learning as a Path to Conversational AI
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Aug 26th 2020
Research Post
Inverse Policy Evaluation for Value-based Sequential Decision-making
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Jun 29th 2020
Research Post
Learning and Planning in Average-Reward Markov Decision Processes
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Jun 23rd 2020
News
The Tea Time Talks 2020: Week One
Watch week one videos of the 2020 Tea Time Talks, featuring Rich Sutton, Csaba Szepesvári, Patrick Pilarski & Martha White.
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May 28th 2020
Research Post
Pavlovian control of intraspinal microstimulation to produce over-ground walking
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Apr 29th 2020
News
Amii Researchers dig deep at renowned international conference ICLR 2020
Amii is proud of our researchers' work being featured at ICLR 2020, running online this year from April 26 to May 1. ICLR is the premier gathering of professionals dedicated to advancing the branch of AI called representation learning, also referred to as deep learning.
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Apr 15th 2020
News
Media Release: Amii greets community leader Cam Linke as new CEO
The Alberta Machine Intelligence Institute (Amii) has welcomed Cam Linke to the role of Chief Executive Officer.
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Apr 9th 2020
News
Recommended Reading: Computers Already Learn From Us. But Can They Teach Themselves?
Richard S. Sutton, Chief Scientific Advisor at Amii, recently took the opportunity to sit down with Craig S. Smith of the New York Times as part of their Artificial Intelligence special report.
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Apr 3rd 2020
Research Post
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning
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Feb 2nd 2018
Research Post
Multi-Step Reinforcement Learning: A Unifying Algorithm
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Feb 9th 2017
Research Post
Multi-step Off-policy Learning Without Importance Sampling Ratios
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May 1st 2016
Research Post
An emphatic approach to the problem of off-policy temporal-difference learning
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Jul 6th 2015
Research Post
Emphatic Temporal-Difference Learning
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Dec 8th 2014
Research Post
Weighted importance sampling for off-policy learning with linear function approximation
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Feb 7th 2014
Research Post
Multi-timescale nexting in a reinforcement learning robot
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Mar 8th 2013
Research Post
Adaptive artificial limbs: a real-time approach to prediction and anticipation
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Feb 21st 2012
Research Post
Temporal-difference search in computer Go
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May 2nd 2011
Research Post
Horde: A Scalable Real-time Architecture for Learning Knowledge from Unsupervised Sensorimotor Interaction
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