6502_65C02_functional_tests
retro
6502_65C02_functional_tests | retro | |
---|---|---|
7 | 6 | |
364 | 3,320 | |
- | 0.4% | |
0.0 | 0.6 | |
about 1 year ago | 3 months ago | |
C | ||
GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
6502_65C02_functional_tests
-
Show HN: Ghidra Plays Mario
Klaus Dormann's 6502 tests don't rely on a particular emulator environment. They could be used with Ghidra.
https://github.com/Klaus2m5/6502_65C02_functional_tests
-
How do I tell if my 65c02 is bad?
How about some assembler code to test all of the opcodes? https://github.com/klaus2m5/6502_65c02_functional_tests
-
I made a cycle accurate profiler for 65C02 assembly with visualizations
https://github.com/Klaus2m5/6502_65C02_functional_tests might be worth a look, it's a comprehensive test suite
-
What's the address of the monitor disassembly routine?
Great! (and not surprising). You may want to look into using a 6520 test suite to check correctness of your emulator, like this one -- note: I have no experience with it, but it took me some time to iron out the last error of my 6502 emulator, and in hindsight I should probably have used such test suite.
- Built a 65C02 emulator
-
Test - Corner cases for 6502 Instructions.
Currently i'm trying to implement 6502's instructions one by one using TDD. I was curious are there any test - corner cases already been written ? I found out ( https://github.com/Klaus2m5/6502_65C02_functional_tests ) but this requires all instructions to be implemented which I don't currently. Is there any way to test a single instruction in isolation for all the edge cases ?
-
Apple //e enhanced ROM oddness
By "bad branch", I mean the emulator takes the wrong branch because it fails to emulate some part of the Apple hardware properly. The 65C02 emulation has passed some pretty stringent tests (https://github.com/Klaus2m5/6502_65C02_functional_tests/blob/master/bin_files/65C02_extended_opcodes_test.lst), so I'm pretty confident in it. But the instruction trace file is around 90,000 lines, so is kinda hard to slog through.
retro
-
Show HN: Ghidra Plays Mario
https://github.com/openai/retro:
> Gym Retro lets you turn classic video games into Gym environments for reinforcement learning and comes with integrations for ~1000 games. It uses various emulators that support the Libretro API, making it fairly easy to add new emulators.
.nes is listed in the supported ROM types:
-
What has replaced OpenAI Retro Gym?
OpenAI Retro Gym hasn't been updated in years, despite being high profile enough to garner 3k stars. It doesn't even support Python 3.9, and needs old versions of setuptools and gym to get installed.
-
Generating expert trajectories for IRL project based on retro NES gym.
The trajectories might not be properly generated (I used a custom wrapper for the retro gym that allows the env to receive human input: Interactive Gym-Retro), so the GAIL agent is just following garbage.
-
Can anyone make OpenAI for Age of Empires 2 Definitive Edition?
You can do it yourself. Maybe with retro
- Need help loading a file for use in a Python script (Gym Retro - Brute)
-
Trying to create an AI that can play a video game.
Another alternative is OpenAI gyms. For example, this supports NES, SNES, and GB.
What are some alternatives?
Gymnasium - An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
ghidra-tlcs900h - Ghidra processor module for Toshiba TLCS-900/H
MO-Gymnasium - Multi-objective Gymnasium environments for reinforcement learning
ghidra-plays-mario - Playing NES ROMs with Ghidra's PCode Emulator
Muzero-unplugged - Pytorch Implementation of MuZero Unplugged for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
switcher - Gnome Shell extension to switch windows quickly by typing
stable-retro - Retro Games in Gym
MAMEToolkit - A Python toolkit used to train reinforcement learning algorithms against arcade games