Summaries of Chapters 2-4 for Game AI Pro 2

Brief Chapter 2 Summary:
What is interesting about the combat dialogue AI in FEAR is that no code was actually ever written for squad reinforcements to arrive when the one live squad member would call for them. The developers admitted that the code in the game for any general first person shooter is to have reinforcements automatically show up after the player has eliminated most of the enemies. What the developers of FEAR did what give the player an illusion of AI which seems to be very common in game AI. Game AI only goes as far to the purpose it needs to serve in the game. In the case of FEAR, it is to serve up more sophisticated dialogue interactions between squad members rather than the usual "bark" (enemy grunts, confirmation of being hit, etc.) the FPS is known for.

Brief Chapter 3 Summary:
This chapter goes over dual-utility reasoning. It is an alternative to boolean based logic that employs heuristic function to evaluate specific situations in game and ensure that the most important or relevant category will be selected. This is an example of game AI that uses heavy programming. Zoo Tycoon 2 employs dual-utility reasoning for its gameplay systems.

Brief Chapter 4 Summary:
Vision Zones and Object Identification Certainty are the main subjects of this chapter. Vision Zones are models used by game agents to identify objects within their periphery. It usually requires three checks: distance, field of view, and raycast to confirm the viewing of objects. All of this done by a boolean-based model of vision which is very limiting for sophisticated game AI. What the author seeks to resolve this is vision zones couple with object identification certainty. OIC will assign values to each vision zone for the player agent to determine whether an object can clearly seen or not. This is similar to a how a human experiences vision where a far away object will be seen, but it is to blurry to identify it. By utilizing OIC, game AI can influence game agents to comment and react to what they are seeing in appropriate ways. However, the main consideration for this system is to consider how many assets (animation, voice, sound effects, etc.,) will need to be supplemented in the game to make this possible. The scope or budget of the game needs to be seriously considered.

What I took from these chapters are the different uses of game AI development and how it may not be as sophisticated as it appears to be. The combat dialogue AI inf FEAR  is a good example. Moving forward I'll continue to look into game AI.


Week 1 - Research narrative systems
Week 2 - Research narrative systems
Week 3 - Research Game AI
Week 4 - Research Game AI
Week 5 - Reframed question towards Game AI.
Week 6 - Find AI and training tools to work with
Week 7 - Pick a primary tool and develop short scenario
Week 8 - Pick a primary tool and develop short scenario
Week 9 - Playtesting and Refinement
Week 10 - Final Results

Game AI Pro Chapter One

I've read through Game AI Pro Chapter One to find out what game AI is. What I find is that game AI, in particular, is still relatively new and programmable through different aspects. The authors of this chapter, Mike Lewis and Kevin Dill, stress that both game design and AI are heavily intertwined in game development field. Indeed, many game designers are "lead AI" or "lead designer" hybrid roles that combine both engineering and game design. In this sense, there is a close relationship in design and programming in game development. The chapter goes on to discuss aspects of game development that involve AI like pathfinding, conversations, dramatic storylines, player modeling, modeling/displaying emotion, social relationships, scale, and content explosion. With game AI, it seems like there's a lot involved in it for game development that involves a heavy amount of programming and ventures to explore as the technology is constantly changing. Because of this, most developers cannot agree on a set concrete definition of game AI. Game AI involves many things. For the sake of my potential research, the venues of game AI I'd like to focus on is conversations and dramatic/emergent storylines. What I understood from this reading is that game AI is still a developing field that is formed for different uses depending on the game.

Week 1 - Research narrative systems
Week 2 - Research narrative systems
Week 3 - Research Game AI
Week 4 - Research Game AI
Week 5 - Reframed question towards Game AI.
Week 6 - Find AI and training tools to work with
Week 7 - Pick a primary tool and develop short scenario
Week 8 - Pick a primary tool and develop short scenario
Week 9 - Playtesting and Refinement
Week 10 - Final Results

1/23/20 A review of interactive narrative systems and technologies: a training perspective

Over the course of the past two days, I've been reading through and considering research into interactive narrative systems and its applications to training. In my potential research, I am considering training in general retail jobs. I've read the research paper by Luo, et al. (2015) that goes over all the more relevant interactive narrative systems that have been developed. What I find interesting is that only one has been developed specifically for military training, ISAT. While others like C-DraGer seem more suitable for retail training due to the ability to generate plot point in a story and it's "case-based" approach. This interactive narrative system will adopt to the player's choices and come up with interesting scenarios that a potential employee may find themselves in a retail environment. Overall, I find the paper to be fruitful in my research of interactive narrative systems, and I will continue into my research with the readings of two books, Game AI Pro 2 and Interactive Narratives and Transmedia Storytelling. Both will strengthen my knowledge of AI and its relation to the future of interactive narratives.

A review of interactive narrative systems and technologies: a training perspective


Week 1 - Research narrative systems
Week 2 - Research narrative systems
Week 3 - Research Game AI
Week 4 - Research Game AI
Week 5 - Reframed question towards Game AI.
Week 6 - Find AI and training tools to work with
Week 7 - Pick a primary tool and develop short scenario
Week 8 - Pick a primary tool and develop short scenario
Week 9 - Playtesting and Refinement
Week 10 - Final Results

First Blog for DIGM 540

Between the dates of 1/6/20-1/8/20, I've been thinking about my potential project for this course. My general idea comes from branching narrative paths. What I've learned during my undergrad at Bloomfield College is that it is generally difficult to develop a game with meaningful branching narratives. Ultimately, it is like developing another game on top of your existing one. For example, if you want certain character interactions to lead to a different pathway based on the player-character's choice, you have to make new assets (art, music, effects), possibly a new gameplay interaction, and dialogue. While working on my undergrad project, I had no choice but to create an illusion of meaningful choice while keeping the game strictly on a linear path. The general idea for my project will be how to make a dialogue system that can make branching pathways easier to develop on a game engine like Unity. Certain apps like Fungus already exist, but how would you make dialogue options more meaningful and robust? Fungus feels a bit limiting, so I would like to improve upon this. The final goal is to eventually go back to improve on projects I have already done based on the potential results of this project.

Week 1 - Research narrative systems
Week 2 - Research narrative systems
Week 3 - Research Game AI
Week 4 - Research Game AI
Week 5 - Reframed question towards Game AI.
Week 6 - Find AI and training tools to work with
Week 7 - Pick a primary tool and develop short scenario
Week 8 - Pick a primary tool and develop short scenario
Week 9 - Playtesting and Refinement
Week 10 - Final Results