Skip to content

Latest commit

 

History

History
99 lines (71 loc) · 2.55 KB

README.markdown

File metadata and controls

99 lines (71 loc) · 2.55 KB
Raw

Description

Qualia is a free software library for embedded AVR agent-based systems written in simple C++.

The software is licensed under the Gnu GPL version 3 (see LICENSE file).

Version

Current version is 0.2.

Authors

Head developer:
Sofian Audry
info(@)sofianaudry(.)com

Windows compliance:
Bruno Angeles

Copyright

Copyright (c) 2011-2012 Sofian Audry (the main author)
This software library is distributed under the Gnu GPL version 3. Please refer to LICENSE file for details.

This software library includes code from the following softwares:

Torch3 : machine-learning library
  Website: http://www.torch.ch/torch3/  
  License: BSD  
  Copyright (c) 2003--2004 Ronan Collobert  
  Copyright (c) 2003--2004 Samy Bengio  
  Copyright (c) 2003--2004 Johnny Mariéthoz

GALib : library of genetic algorithm components  
  Website: http://lancet.mit.edu/ga/  
  License: BSD  
  Copyright (c) 1995-1996 Massachusetts Institute of Technology (MIT)  
  Copyright (c) 1996-2005 Matthew Wall (the Author)

Libbehavior : reactive AI library based on the concept of "behavior trees"  
  Website: http://code.google.com/p/libbehavior/  
  License: New BSD License

Thanks

This project is realized with the support of CINQ as part of the Emerge research project with LabXmodal (Concordia Univeristy, Montréal), IDMIL (McGill University, Montréal) and Moment Factory (Montréal).

Objectives

  1. Allow to easily switch between different environments
  • Two modes: simulation (computer) vs embedded (AVR).
  • The agent should stay the same.
  • Interchangeable environment simulation vs embedded
  • Easy switch between the two modes
  1. Well-managed on AVR chips
  • Low memory trace (Flash and SRAM)
  • Static allocation
  1. Modular
  • Agent can stay the same while environments are exchanged
  • eg. easy switch of reward function (reinforcement learning)
  1. Multi-paradigm
  • Procedural
  • FSM
  • Reinforcement learning

Compiling

Standard build (eg. on i386 platforms): $ scons

Build for AVR (release mode): $ scons platform=avr mode=release

Build for Arduino (debug mode): $ scons platform=arduino mode=debug

Cleaning up (example): $ scons platform=arduino --clean

To compile examples, go to the example folder and run scons. The qualia library needs to be compiled first.

Installing

See INSTALL file for installation procedure on standard (PC) platform.