For the interested people: We base all on our work on the "Causal Entropic Forces" by Alexander Wissner-Gross and apply the ideas outlined in the G.A.S. algorithm. We are not actually learning in any way, so all games are independent from each other and first-ever played game is as godd as the 100th game.
First, we list the already finished environments. They include 100 games played and an official scoring in OpenAI gym as the average of those 100 games:
1. Atari - MsPacman-ram-v0: average score of 11.5k vs 9.1k (x1.2)
This was the first env. to be finished and uploaded, so it represent our first official record. We decided to use the "ram" version (instead of the image version) because it is irrelevant for our algorithm but not for a more standard approach, so we had an extra punch.
The main issue here was a dead Pacman takes about 15 frames to be noticeable on screen (there is a short animation) so you need to think in advance at least those 15 frames (ticks) in order to start detecting death.