Managing Massive Multiplayer Online Games (sose18) | VideoOnline

Chapter 9: Artificial Intelligence (cont.)

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(00:00:00) >: Chapter 9: Artificial Intelligence – Overview

(00:05:26) >: Information regarding final exam

(00:06:12) >: Recap Chapter 9

(00:50:44) >: Function Approximation

(01:13:38) >: Examples (OpenAI Gym)

(01:18:18) >: Why is AI important for Games?

(01:28:54) >: Imitation Learning

(01:39:45) >: Antagonistic Search

(01:52:16) >: Min-Max Search // Alpha-Beta Pruning

(02:04:06) >: Monte Carlo Tree Search

(02:18:23) >: Chapter 9 – Learning Goals and Literature

Date: 03.07.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 8: Ranking Skill (rep.) // Chapter 9: Artificial Intelligence

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(00:00:00) >: Recap Chapter 8

(00:19:29) >: Chapter 9: Artificial Intelligence – Overview

(00:23:47) >: What is Artificial Intelligence?

(00:24:44) >: Environments // Agents

(00:37:00) >: Sequential Decision Making // Deterministic Sequential Planning

(00:51:02) >: Routing in Open Environments // Visibility Graph // Expansion with Start- and Goal-Nodes

(00:57:32) >: Dijkstra’s Algorithm

(01:01:06) >: A*-Search

(01:07:34) >: Visibility Graph for extended Objects

(01:12:00) >: More Pathfinding Methods

(01:14:09) >: Markov Decision Process

(01:17:44) >: Motivation non-deterministic Routing // Policies and Utilities

(01:24:18) >: Bellman’s Equations

(01:27:58) >: Policy Iteration // Policy Evaluation // Value Iteration

(01:37:31) >: MDP Synopsis // Model-Free Reinforcement Learning

(01:46:53) >: Monte-Carlo Policy Evaluation

(01:53:28) >: Temporal Difference Learning

(01:57:44) >: Policy Optimization // Samples and Policy Updates

(02:05:49) >: Learning on a Queryable Environment

(02:09:37) >: Epsilon-Greedy Exploration

(02:11:29) >: On-Policy and Off-Policy Learning // Q-Learning

Date: 26.06.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 7: Spatial Analytics (cont.) // Chapter 8: Ranking Skill

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(00:00:00) >: Information regarding final exam

(00:01:31) >: Recap Chapter 7

(00:07:30) >: Spatial Data Mining // Spatial Outlier Detection

(00:17:10) >: Trajectories

(00:21:38) >: Distance Measures for Trajectories // LCSS Similarity

(00:30:32) >: Compressing Trajectories // Douglas-Peucker Algorithm

(00:40:46) >: Pattern Search in Trajectories

(00:42:13) >: Flocks

(00:57:48) >: Encounters

(01:19:13) >: Chapter 7 – Learning Goals and Literature

(01:20:03) >: Chapter 8: Ranking Skill – Overview

(01:22:12) >: Models for play level

(01:29:17) >: The ELO System // Updating the ELO Ranking

(01:42:09) >: True Skill

(01:59:56) >: Team Skill

(02:13:33) >: Conclusion // Alternative Approach

(02:18:20) >: Chapter 8 – Learning Goals and Literature

Date: 19.06.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 6: Temporal Analysis (cont.) // Chapter 7: Spatial Analytics

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(00:00:00) >: Recap Chapter 6

(00:19:47) >: Markov Chains and Sequences

(00:32:23) >: Hidden Markov Models

(00:42:15) >: Use of HMM – Evaluation: Forward Variables

(00:54:12) >: Use of HMM – Recognition: Viterbi Algorithm

(00:57:32) >: Use of HMM – Training: Baum-Welch Estimation

(01:12:14) >: Real-Value Sequences

(01:15:42) >: Time series

(01:25:08) >: Discrete Fourier Transformation (DFT)

(01:37:23) >: Distances of Time Series // Dynamic Time Warping Distance

(01:43:44) >: Statistic Models for Time // Homogeneous Poisson Processes

(01:47:58) >: Parameter assessment

(01:50:54) >: Chapter 6 – Learning Goals and Literature

(01:52:09) >: Chapter 7: Spatial Analytics – Overview

(01:54:23) >: Spatial Data Mining and Games

(01:57:41) >: Tasks of Spatial Game Analytics

(02:02:45) >: Spatial Data and Visualization

(02:04:25) >: Heat Maps

(02:08:38) >: Kernel density estimator

Date: 12.06.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 5: Game Analytics (cont.) // Chapter 6: Temporal Analysis

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(00:00:00) >: Recap Chapter 5

(00:15:11) >: Supervised Learning (cont.)

(00:27:38) >: Instance-based Learning

(00:34:35) >: Bayesian Learning

(00:52:53) >: Univariate Distributions // Statistical Models

(01:06:32) >: Evaluating Supervised Learners // Testing Supervised Predictors

(01:15:11) >: Stratified k-fold Cross Validation

(01:19:10) >: Evaluating Classification Results // Classification Metrics

(01:29:17) >: Chapter 5 – Learning goals

(01:29:33) >: Chapter 6: Temporal Analysis – Overview

(01:30:14) >: Player Behavior

(01:36:03) >: Subsequences and Partitioning // Frequent Subsequence Mining

(01:44:05) >: Suffix Trees

(01:58:01) >: Comparing two Sequences

(02:00:23) >: Levenshtein Distance

(02:10:51) >: Edit Distances

Date: 05.06.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 5: Game Analytics

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(00:00:00) >: Chapter 5: Game Analytics – Overview

(00:02:36) >: Why Game Analytics?

(00:07:30) >: What is Game Analytics?

(00:14:48) >: Knowledge Discovery on Game Data

(00:20:26) >: E-Sports Analytics

(00:30:27) >: Why are Players committing fraud?

(00:41:59) >: Technical and other ways to cheat

(01:07:30) >: Countermeasures

(01:21:17) >: Monitoring player behavior

(01:25:36) >: Game Balance

(01:41:41) >: The Analytical Process in Games

(01:49:49) >: When does Game Analytics work?

(01:54:04) >: Overfitting // Feature Space, Distance and Similarity Measure

(02:00:51) >: Formal definition of distance function // Vectors as Object Presentation

(02:04:50) >: Supervised Learning

Date: 29.05.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 3: Distributed Game Architectures (cont.) // Chapter 4: Data Persistence

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(00:00:00) >: Recap Chapter 3

(00:27:48) >: Thoughts on Client-Server Communication

(00:31:52) >: Requirements of Computer Games

(00:37:30) >: Protocols and Communication Solutions

(00:47:42) >: Learning Goals and Literature

(00:50:25) >: Chapter 4: Data Persistence – Overview

(00:52:15) >: Need for Persistence

(00:58:58) >: Persistence Layer Requirements

(01:04:45) >: Methods for Replays and Save Games: State-Log, Transition-Log, Action-Log

(01:23:16) >: Save Games in MMOs

(01:29:14) >: MMOGs and Relational Databases, Persistence via Log-files

(01:39:45) >: Open Issues

(01:43:15) >: Check-Point-Recovery Methods

(02:10:16) >: Discussion

(02:14:54) >: Learning Goals and Literature

Date: 15.05.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 2: The Game Core (cont.) // Chapter 3: Distributed Game Architectures

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(00:00:00) >: Recap Chapter 2

(00:24:22) >: Insert, Delete, Bulk-Load (cont.)

(00:38:35) >: Throw-Away Indices, Problems of Data Volatility

(00:42:36) >: Query Processing: Range-Query, NN-Query and Spatial Joins

(00:52:44) >: Game Design

(00:56:23) >: What you should know by now...

(00:59:20) >: Chapter 3: Overview

(01:03:24) >: MMOG Architectures, Detailed Client Server Architecture

(01:19:41) >: Distributing the Game Core, Protocol Content

(01:25:46) >: Thin Client Solution, Fat Client Solution

(01:33:16) >: Problems of Centralized and Decentralized Computation

(01:39:17) >: Local Time

(01:50:26) >: Application in Games

(01:57:32) >: Spatial Movement, Dead Reckoning

(02:12:24) >: Thoughts on Client-Server Communication

Date: 08.05.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 2: The Game Core (cont.)

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(00:00:23) >: Chapter Overview

(00:01:02) >: Recap

(00:03:51) >: Game State

(00:04:54) >: Actions

(00:32:39) >: Physics Engines

(00:40:10) >: Spatial Management in Game Servern

(01:01:40) >: Sharding and Instantiation

(01:09:19) >: Zoning

(01:22:55) >: Classic Index Structures

(01:30:32) >: Important Features of Search Trees

(01:36:40) >: Requirements for an MMO Server

(01:41:53) >: Binary Space Partitioning Trees (BSP-Tree)

(01:53:18) >: R-Tree

(02:02:58) >: Bulk-Loads within R-Space

Date: 24.04.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 2: The Game Core

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(00:00:15) >: Repeat: Chapter 1

(00:41:46) >: Chapter 2: The Game Core

(00:41:47) >: Chapter Overview

(00:58:58) >: Time Models for Action Processing

(01:36:05) >: Actions vs. Transactions

(01:45:02) >: The Game Loop

(02:06:21) >: Physics Engines

Date: 17.04.2018

Lecturer: Prof. Dr. Matthias Schubert

Chapter 1: Computer Games

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(00:00:07) >: Why study Games?

(00:11:34) >: Social Aspects of Computer Games

(00:15:43) >: Business Models

(00:56:03) >: Distinction of Games

(01:13:13) >: Classic Game Genres

(01:37:31) >: More Genres

(01:39:21) >: Structure of Computer Games

(01:52:22) >: Building Blocks in Game Architecture

(01:56:33) >: Lecture Overview

Date: 10.04.2018

Lecturer: Prof. Dr. Matthias Schubert

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