Reading List - SioKCronin/sio_dojo GitHub Wiki
2018
Q2
BOOKS
- Introduction to Linear Algebra - Serge Lang
- Reinforcement Learning - Sutton & Barto (1998)
- Algorithm Design Manual - Skiena
- Practical Algorithms and Data Structures
- Algorithms for Reinforcement Learning
- MDPs in AI
ARTICLES
- Lots of PSOs (check related projects)
- Lots of RLs (check related projects)
VIDEOS
- Berkeley CS188 - Intro to AI
- 3Blue1Brown Linear Algebra
- Deep RL Bootcamp
- Approximate Dynamic Programming
Q1
BOOKS
- Gaussian Processes for Machine Learning - Rasmussen & Williams (2006)
- Swarm Intelligence - Kennedy & Eberhart (2001)
ARTICLES
- Swarm Reinforcement Learning Algorithms Based on Particle Swarm Optimization
- Autonomous Agent Response Learning by a Multi-Species Particle Swarm Optimization
- Adam: A method for stochastic optimization
- Portfolio Allocation for Bayesian Optimization
- Introduction to Gaussian Processes - David Mackay (1998)
- Practical Bayesian Optimization of Machine Learning Algorithms - Snoek, Larochelle, & Adams (2012)
- Taking the Human Out of the Loop: A Review of Bayesian Optimization - Shahriari et al (2016)
2017
BOOKS
- Computer Age Statistical Inference: Algorithms, Evidence and Data Science - Bradley Efron & Trevor Hasties
- Introduction to the Theory of Computation - Michael Sipser (3rd edition - 2013)
- More Precisely: The Math You Need to Do Philosophy - Eric Steinhart (2009)
- How to Read and Do Proofs - Daniel Solow (2005)
ARTICLES
- Swarm Intelligence in Big Data Analytics by Shi Cheng et al. (2013)
- Swarm Intelligence Systems for Transportation Engineers
- Representational Learning: A Review and New Perspectives by Yoshua Bengio et al. (2014)
- Safely Interruptible Agents by Laurent Orseau and Stuart Armstrong (2016)
- Continuous Time Bayesian Networks by Uri Nodelman et al.
- A Computational Model of Machine Consciousness - J. Starzyk & D. Prasad(2010)
- Learning the Preference of Bounded Agents