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AP Computer Science A

Known as: Grid World, GridWorld, GridWorld Case Study 
Advanced Placement Computer Science A (also called AP Java) is an AP Computer Science course and examination offered by the College Board to high… 
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AP Computer ScienceAbstract data typeAlgorithmArray data structure

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning
There is a long history of using meta learning as representation learning, specifically for determining the relevance of inputs… 
2016
2016
Collecting a swarm in a grid environment using shared, global inputs
This paper investigates efficient techniques to collect and concentrate an under-actuated particle swarm despite obstacles… 
Review
2015
Review
2015
Achieving a shared goal with AP Computer Science A and AP Computer Science Principles
College Board has joined national efforts to improve the state of STEM education, in particular to address the challenge of… 
2014
2014
Online State Elimination in Accelerated reinforcement Learning
Most successes in accelerating RL incorporated internal knowledge or human intervention into the learning system such as reward… 
2013
2013
Il "m'ama non m'ama" con il teléphilon (Theocr. 3, 29; Poll. 9, 127; Agath. AP V 296)
2009
2009
Interoperable processing of digital elevation models in grid infrastructures
Based on the service specifications of the Open Geospatial Consortium (OGC), Spatial Data Infrastructures (SDI) support the… 
2007
2007
A Knowledge Representation and Reasoning Based on Petri Nets with Spatio-Temporal Tokens
Knowledge representation of time and space, and reasoning about temporal and spatial relations, are important areas in fields… 
2004
2004
Stabilization of Biped Robot based on Two mode Q-learning
Abstract In this paper, two mode Q-learning, an extension of Q-learning, is used to stabilize the Zero Moment Point (ZMP)of a… 
1995
1995
Fast and feasible reinforcement learning algorithm
It is desirable that agents can determine themselves the next action to execute, using fast and feasible learning algorithm to… 
Highly Cited
1990
Highly Cited
1990
A new approach to unsupervised learning in deterministic environments
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