• Anticipatory Behavior of Software Agents in Self-Organizing Negotiations

• A Contract Decommitment Protocol for Automated Negotiation in Time Variant Environments

• An Agent-based Dynamic Information Network for Supply Chain Management

• Internalising Interaction Protocols as First-Class Programming Elements in Multi Agent Systems

• Developing multi-agent systems with a FIPA-compliant agent framework

• Multi-Agent Forex Trading System

• Multi-Agent Reinforcement Learning for Automated Peer-to-Peer Energy Trading in Double-Side Auction Market

• Modelling Stock Markets by Multi-agent Reinforcement Learning

• Application of signal processing to the analysis of financial data [In the Spotlight]

• Deep Robust Reinforcement Learning for Practical Algorithmic Trading

• Algotrading Documentation done by HKU

• Modelling Stock Markets by Multi-agent Reinforcement Learning

• Application of signal processing to the analysis of financial data [In the Spotlight]

Reinforcement Learning:

• RL on Stock Data

• risk-averse reinforcement learning for algorithmic trading

• Using Reinforcement Learning in the Algorithmic Trading Problem

• Math of Q-Learning — Python

• Python Trading Toolbox: a gentle introduction to backtesting

• How to Perform Backtesting in Python

• How to retrieve LIVE stock market data via WebSockets in Python 

• Portfolio Optimization using Reinforcement Learning

• Deep Reinforcement Trading with Predictable Returns

• Portfolio Optimization with Python using Efficient Frontier with Practical Examples

• Deep Direct Reinforcement Learning for Financial Signal Representation and Trading

Links in 2022:

• Machine Learning for Trading: From Idea to Execution

Seq2Seq:

• https://www.youtube.com/watch?v=MqugtGD605k

• Seq2Seq Models

• https://github.com/lukas/ml-class/blob/master/videos/seq2seq/train.py

• https://github.com/somvirs57/seq2seq_methematic_sum/blob/master/summation.ipynb

• https://blog.keras.io/a-ten-minute-introduction-to-sequence-to-sequence-learning-in-keras.html

• https://towardsdatascience.com/understanding-encoder-decoder-sequence-to-sequence-model-679e04af4346

• https://web.stanford.edu/~jurafsky/slp3/

Reinforcement Learning:

• Training RL to do Cartpole Balancing

• Reinforcement Learning — Implement TicTacToe

• Dueling Network Architectures for Deep Reinforcement Learning

• Visualizing and Understanding Atari Agents

• Implementation and Comparison of Occlusion-based Explainable Artificial Intelligence Methods

• Visualizing and Understanding Convolutional Networks

• Playing Atari with Deep Reinforcement Learning 

• Video Course from Simonini

• Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms

• Reinforcement Learning: A Tutorial

• Visualizing and Understanding Atari Agents

• Explainable Reinforcement Learning: A Survey

• Graying the black box: Understanding DQNs

• Autonomous Self-Explanation of Behavior for Interactive Reinforcement Learning Agents

• Efficient Saliency Maps for Explainable AI

• Practical Guide for Visualizing CNNs Using Saliency Maps

• Effective Communications: A Joint Learning and Communication Framework for Multi-Agent Reinforcement Learning over Noisy Channels

• Maximum Entropy Deep Inverse Reinforcement Learning

• Deep Deterministic Policy Gradient (DDPG) algorithm

• Effective Diversity in Population Based Reinforcement Learning

• Zero-Shot Visual Imitation

• Fairness in Reinforcement Learning

• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Maximum Likelihood and Bayesian Classifiers

• The Math Behind Bayesian Classifiers Clearly Explained!

• Naive Bayes, Clearly Explained!!!

AdaBoost/Boosting

• Feature Learning Viewpoint of AdaBoost and a New Algorithm

• AdaBoost Algorithm Tutorial

• Adaboost for Dummies: Breaking Down the Math (and its Equations) into Simple Terms

• Explaining AdaBoost

• Best Clear Explanation about AdaBoost on Youtube

• Boosting algorithm: AdaBoost

Neural Network

• Backpropagation and the brain

Latent Variables Method: 

• https://www2.cs.sfu.ca/~oschulte/teaching/726/spring11/slides/mychapter9.pdf

• https://towardsdatascience.com/latent-variables-expectation-maximization-algorithm-fb15c4e0f32c

Recommended Research Articles about Process Mining

• Process Mining of Five Dutch Municipalities ’ Building Permit Application Process : The Value Added in E-Government The BPI Challenge 2015

• An Analysis of Cargo Release Services with Process Mining: A Case Study in a Logistics Company

• Business Process Mining in Warehouses: a Case Study

• Process Mining in the Large: A Tutorial

• A Case Study on the Business Benefits of Automated Process Discovery

• Process discovery from event data: Relating models and logs through abstractions

• Enabling Process Mining in Aircraft Manufactures: Extracting Event Logs and Discovering Processes from Complex Data

Recommended Research Articles about Process Mining

• Single-Image Super-Resolution: A Benchmark

• Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model

• Single Image Super-Resolution via a Holistic Attention Network

• RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution

• Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

• Deep Learning for Single Image Super-Resolution

• Fast and Accurate Single Image Super-Resolution via Information Distillation Network

• Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination

• Fast and Accurate Single Image Super-Resolution via Information Distillation Network

• EigenGAN: Layer-Wise Eigen-Learning for GANs

• Real-World Single Image Super-Resolution

Recommended Articles about Game Theory

• An Overview of Cooperative and Competitive Multiagent Learning

• Why are Coke and Pepsi never on sale at the same time? An answer from game theory 

• Game Theory Examples Part 2: Why Price Matching Is Good For Businesses 

• Game Theory with Python

• Making game theory work for managers

• SOCIAL PSYCHOLOGY AND MARKETING: THE CONSUMPTION GAME. UNDERSTANDING MARKETING AND CONSUMER BEHAVIOR THROUGH GAME THEORY

• Game theory in marketing science uses and limitations

• Analysis of Geoinformation Pricing Using Game Theory

• Game Theory Models of Pricing

• Product price control using game theory: A case study of a fish price in the state of Terengganu

• Game Theory Models of Pricing

• Lecture Notes from MIT 

• Price vs Quantity in a Duopoly Supergame with Nash Punishments

• Why are Coke and Pepsi never on sale at the same time? An answer from game theory 

• Game Theory Examples Part 2: Why Price Matching Is Good For Businesses

• The Cournot outcome as the result of price competition

• Price Discrimination in Dynamic Cournot Competition

• Price-Matching Guarantees

• MORE AMAZON EFFECTS: ONLINE COMPETITION AND PRICING BEHAVIORS

• Game Theory Analysis of E-Commerce’s Price War

• Game Theory Term Paper – “E-Commerce Discount Wars (Myntra vs. Jabong)

• The Evolution of Price Competition Game on Complex Networks

• An Empirical Game-Theoretic Analysis of the Dynamics of Cooperation in Small Groups

• Principal Component Analysis with NumPy

• Data Science for E-Commerce with Python

• Rewriting SQL Queries with Pandas

• Why you should use User Stories in Data Analytics

• Text Generation With Python And GPT-2

• 7 Must Know SQL Querying Mistakes & Fixes

• A Collection of Advanced Data Visualization in Matplotlib and Seaborn

• Insights from Visualizing Public Data on Twitch

• Essential SQL Skills for Data Scientists in 2021

• Foundations in Analytics: The Importance of Scale

• Support Vector Machines under the hood

• How to convert JSON into a Pandas DataFrame