Archive for the 'planning' Category

Interactive Objects in Gaming Applications (Sapienza University of Rome-2013)

I am teaching a topics course with Prof. Marco Fratarcangeli about “Interactive Objects in Gaming Applications: Basic principles and practical scenarios using the Unity platform”, in which I am covering the part about how objects can exhibit behavior. In particular I focus on i) Pathfinding ii) Action-based decision making, and iii) AI Architectures.

i) Pathfinding

Overview

The lectures about path planning (or pathfinding) can be found on slideshare: Pathfinding-Part1, Pathfinding-Part2, Pathfinding-Part3. Also, the Unity code examples of Part 2 (based on Aron’s Pathfinding and Unity’s 3D Platformer Tutorial) can be found here: Pathfinding-Unity.zip

Information about the material will be updated as we go, as well as a long list of references.

Abstract of the course:

The course aims at providing a hands-on introduction on the basic principles as well as state-of-the-art methods and techniques for building interactive objects in video games. Each of the aspects examined will be presented both in a theoretical framework that allows studying related research problems as well as in a practical setting providing the tools needed for a real-world implementation. For the latter we will rely mostly on Unity, a popular game engine that is becoming an emerging standard for indie game development. The course is divided in two main themes: one that focuses on the physical aspect of the behavior of interactive objects, and one that focuses on the artificial intelligence aspect of the behavior of smart objects.

In the first part we will introduce the basic concepts for the development of interactive applications, including logic, rendering, physics, audio, user interaction and graphical interface. We will map each of these concepts in their practical implementation by using the Unity toolset.

In the second part we will continue with some of the most widely used methodologies that allow smart objects and non-player characters (NPCs) to exhibit autonomy and flexible behavior through various forms of decision making, including techniques for pathfinding, reactive behavior through automata and processes, and goal-oriented action planning.

Video-games and more in the upcoming “Planning in Games ICAPS-2013 Workshop” (PG-2013)

Interested in applications of AI planning techniques to video-games and more? Take a look at the upcoming Planning in Games Workshop at ICAPS-2013 to take place in Rome!

The workshop aims at gathering researchers and practitioners interested in the use of planning in games to discuss current work and future directions: from classic games to video games, from academia to the industry, from researchers to developers and designers to gamers, from path planning to strategic planning, and more.

PG-2013-Poster-Web(medium)

Call for papers

Topics and Objectives

The Planning in Games Workshop covers a wide range of topics related to developing, integrating, and benchmarking single agent, adversarial, and multi-agent planning techniques into classic games as well as video games. While the emphasis of the workshop is on the methods and techniques developed in the field of AI, the workshop aims at bringing together researchers and practitioners involved in applications of planning in the field of video games, to discuss current work and future directions. We especially welcome discussions and demonstrations of existing systems.

Artificial Intelligence Planning is successfully used in video-games: heuristic-based STRIPS-like planning and HTN Planning generate character behavior in several fast paced games since 2005, reaching millions of players. This certainly does not make planning in games a solved problem: from new game genres to next-generation consoles and new markets such as cloud gaming, the AI Planning research frontier is wide and open to any kind of planning technique in a gaming context.

This 3rd edition of the ICAPS Workshop on Planning in Games shall acknowledge the tighter link with the video-game industry, while aiming at inspiring traditional Game AI Planning research such as optimal planning in huge search spaces and temporal reasoning, and traditional games such as go and chess: this workshop invites submissions on any aspect of AI planning in the largest possible domain of games.

Relevant topics include:

  • Strategic and tactical planning
  • Planning techniques for abstract games such as board games,
  • Planning for command hierarchies
  • Temporal and spatial planning
  • Real-time planning and replanning
  • Drama and story planning
  • Checking and debugging game design with planning
  • Cloud-based planning services
  • Plan recognition, cased-based and crowd-sourcing planning
  • Abstractions and representational issues
  • Competitions

Like previous Planning in Games workshops, we hope PG-2013 to be a highly participatory and discussion-oriented forum. We anticipate a one-day workshop that will comprise of several sessions including presentations of research papers, position papers, and posters, and a panel discussion.

Invited Talks

  • Dana S. Nau (University of Maryland)
  • Alex Champandard (AIGameDev.com)
  • William van der Sterren (CGF-AI)

Submissions

Potential participants are invited to submit either a full
length technical paper or a statement of interest with a position
paper. Submissions are accepted in PDF format only, using the AAAI
formatting guidelines at:
http://www.aaai.org/Publications/Author/author.php.

Submissions must be no longer than seven (7) pages in length,
including references and figures. Author names should be included.
Overlength papers will not be accepted for publication. Papers must
be submitted electronically in PDF format by the due date.

Submission website:
https://www.easychair.org/conferences/?conf=pg2013.

Electronic proceedings will be offered to delegates in a USB key
by ICAPS-2013, and will also be published online in the ICAPS-2013
website.

Deadlines

Submission deadline: March 23, 2013
Notification: April 20, 2013
Final version: May 10, 2013
Workshop date: June 11, 2013 (TBC)

Workshop Program Chairs

Program Committee

  • Marc Cavazza, University of Teesside, United Kingdom
  • Carle Cote, Eidos, Canada
  • Luke Dicken, University of Strathclyde, United Kingdom
  • Alan Fern, Oregon State University, United States
  • Peter Gregory, University of Teesside, United Kingdom
  • Carlos Linares López, Universidad Carlos III de Madrid, Spain
  • Christian Muise, University of Toronto, Canada
  • Héctor Muñoz Ávila, Lehigh University, USA
  • Jeff Orkin, MIT Media Lab, United States
  • Julie Porteous, University of Teesside, United Kingdom
  • Mark Riedl, Georgia Institute of Technology, USA
  • William van der Sterren, CGF-AI, Neatherlands

Real-time Action Planing with Preconditions and Effects (GameCoderMag-2012)

I wrote an article for the March issue of the Game Coder Magazine:

Abstract: In this article I will be covering an artificial intelligence (AI) technique for decision making that can be used in various parts of game development to account for “thinking before acting”. The technique is called Classical Planning in academic AI research, and is one of the most basic approaches for deliberating about the effects of actions and the way the properties of a given domain change under these effects. Variants of this technique have been used successfully in game development under the name Goal Oriented Action Planning (GOAP), each time focusing on a different aspect of this technique, adopting it for the particular needs of the game.

You can get the article here.

More information: In the article I go over a simple example inspired from real-time strategy games. I focus on the behavior of a peasant that can be instructed to bring food or handle other resources, and extend the character’s functionality so that they can take more advanced commands which may need a series of actions to be realized. Using this example I go over one of the simplest forms of planning, that is propositional STRIPS planning, and present an implementation using Python.

The following screenshots are code listings included in the article, which show how the planning algorithm can help the peasant find ways to realize the given commands. 

The self-contained Python code can be found here: PyPlan. The file goap.py contains all the necessary classes and methods for implementing planning, and example.py includes a simple example based on the peasant scenario that is explained in detail in the article.

Bibtex:

@article{vassos12gamecoderplanning,
author = {Vassos, Stavros},
citeulike-article-id = {11193150},
citeulike-linkout-0 = {http://stavros.lostre.org/files/Vassos12ActionPlanning.pdf},
journal = {GameCoder Magazine},
keywords = {goap, planning, strips, video\_games},
month = mar,
number = {3},
pages = {20–27},
title = {Real-time Action Planing with Preconditions and Effects},
url = {http://stavros.lostre.org/files/Vassos12ActionPlanning.pdf},
year = {2012}
}

NPCs with Artificial Intelligence: From FSMs to BTs to GOAP (GameExpo-2012)

On Friday March 16, I gave a talk at the IEEE Patras Games Expo 2012, which was organized by the IEEE Computer Society Student Chapter in collaboration with the IEEE Student Branch of University of Patras.

My talk was related to artificial intelligence (AI) techniques for specifying the behavior of non-player characters (NPCs) in video games. As a quick introduction to the main ideas behind the most common techniques that have been used in commercial video games, I went over three approaches: Finite State Machines (FMSs), Behavior Trees (BTs), and Goal-Oriented Action Planning (GOAP). The intention was to introduce students to the ideas and highlight what I consider to be the past, the present, and the future of techniques for NPC behavior.

The slides of my talk (in Greek) can be found  here. Some examples in the slides are taken from the book Artificial Intelligence for Games by  Ian Millington, and John Funge, an excellent resource for all types of AI methods for game development.

 

Talk about SimpleFPS at SRI International, Menlo Park, CA (2011)

On Friday October 14, I gave a talk about some preliminary work on building a PDDL benchmark for First-Person Shooter games at SRI International’s Artificial Intelligence Center, Menlo Park, CA USA, 2011.

The talk was based on the following workshop paper I presented at AIIDE-2011: The SimpleFPS Planning Domain: A PDDL Benchmark for Proactive NPCs.

The details of the talk can be found here. The slides of my presentation can be found here.

The SimpleFPS Planning Domain: A PDDL Benchmark for Proactive NPCs (INT4-2011)

The SimpleFPS Planning Domain: A PDDL Benchmark for Proactive NPCs, Stavros Vassos, and Michail Papakonstantinou, In Proceedings of the Non-Player Character AI workshop (NPCAI-2011) of the Artificial Intelligence & Interactive Digital Entertainment (AIIDE-2011) Conference, Stanford CA, USA, 2011.
[pdf | citeulike| slides | slideshare]
Continue reading ‘The SimpleFPS Planning Domain: A PDDL Benchmark for Proactive NPCs (INT4-2011)’

Planning in video games seminar at Hellenic Artificial Intelligence Summer Scholl (HAISS-2011)

Earlier today I gave a seminar about planning and possible applications in video games in the 2nd Hellenic Artificial Intelligence Summer School (HAISS-2011) that was organized by the Hellenic Artificial Intelligence Society (EETN) and the Technoesis network of  the University of Patras, in Patras, Greece.

The slides of my talk (in Greek) can be found  here and the PDDL files mentioned in the talk can be found here. The planner used for the demo is BlackBox which can be found here (for windows use this executable and install the Cygwin DLL or make sure that cygwin1.dll is at the same folder as the BlackBox executable).

The abstract of the talk follows (in Greek).

Πρώτο μέρος: Εισαγωγή στην αναπαράσταση προβλημάτων σχεδιασμού (planning) με βάση τη γλώσσα STRIPS. Προέλαση, οπισθοχώρηση, και ευρετικές συναρτήσεις για την εύρεση λύσης σε προβλήματα σχεδιασμού με βάση την αναζήτηση. Αναπαράσταση προβλημάτων σχεδιασμού στην τυπική γλώσσα PDDL και χρήση του planner BlackBox για την επίλυση προβλημάτων σχεδιασμού στο πεδίο του puzzle game Sokoban.

Δεύτερο μέρος: Εισαγωγή στην ανάπτυξη τεχνητής νοημοσύνης για χαρακτήρες (non-player characters) σε video games και εφαρμογές τεχνικών σχεδιασμού σε εμπορικά video games. Αναπαράσταση των βασικών στοιχείων ενός First-Person Shooter game σε PDDL από την οπτική ενός αντίπαλου χαρακτήρα στον κόσμο του παιχνιδιού, και χρήση του planner BlackBox για την επίλυση προβλημάτων σχεδιασμού που σχετίζονται με τις επιλογές του χαρακτήρα στο παιχνίδι. Σύντομος σχολιασμός επιπλέον τεχνικών όπως η παρακολούθηση εκτέλεσης και ο επανασχεδιασμός.