The term classical AI and symbolic AI is often used to describe a certain period in AI research, mostly before the advent of neural networks and behavior based robotics. This kind of understanding summarizes all efforts in the early years under the same description. But at the same time is leaves out what the word “symbolic” means.
I've investigated the problem in the literature and found that symbolic AI is equal to symbolic planning..And this is equal to high level planning in which the STRIPS language is the most important tool. As a result, GOFAI is not over but it's state of the art AI if the focus is on the higher leyer of a robot control system.
After this theoretical introduction it make sense to give some details for symbolic planning. Suppose there is a game of robocup which is played by a robot swarm. On the bottom side there is the need of low level control and low level sensor interpretation. This kind of tasks is ignored in the following description. Instead the more interesting aspect of the problem is to control the robots on a higher level. Which means to plan the general strategy and long term tasks. Before symbolic AI can be formlized some kind of abstract simulation is needed. This is a simplified robocup simulation in which all the details are missing. It doesn't work with a physics engine, but with a symbolic engine. In most cases the game will look like an early Commodore 64 which contains of low resolution graphics or the extreme case no graphics at all, but a textual menu in which the player can play soccer.
On the first look this kind of simulation is step backward, because it doesn't contains a colorful highly realistic simulation. Instead the game is played on a 10x8 pixel map and the movements of the ball are abstract. The advantage is, this kind of simulations are easily to play autonomously by an AI. The state space is reduced and the allowed actions are working on a higher level. The advantage is, that the computational requirements are low.
Atari 2600 games
A less powerful computer than the Commodore 64 was the Atari 2600 device. It has a maximum resolution of 160x192 pixels but many games are using a smaller resolution. The amount of colors was small and the RAM was 128 bytes. For today's eyes the games on the Atari 2600 are equal to a joke. They doesn't have interesting sound, they are not using 3d graphics, and the movements are unrealistic and slow. What all the games from this area have in common is a low state space. If the map is limited, the amount of possible paths is reduced too. This is equal to a symbolic game.
If the goal is to simplify the game more, the next lower step would be avoid any kind of graphics, and create games in the textmode which are using at maximum only 80 Bytes. According to a fan forum there were few text adventures released, for example “Dark Mage” Another game is “STELLAR TRACK” which was rated by the gamers as poor. The user has to control a spaceship. In detail he sets the maximum warp speed and the feedback is shown on the screen textual.
For explaining what symbolic AI is, the “Stallar Track” game is ideal. It contains of a map which is 8x8 pixel large, everything is in textmode and the overall game is very limited. That means, the player can choose between a small number of actions and after a short period the game gets boring. The advantage is, this sort of domains can be easily simulated and solved by an AI player. He can use a fixed strategy or try to test out alternatives with monte carlo tree search. We can summarize, that symbolic AI has to do with a certain sort of game engine which is a very reduced one. The game engines uses not more than 100 bytes of RAM and the output is given in textual screens.
Turn based strategy games
Before the advent of Real time strategy games, there was a period in computer gaming history which were devoted to turn based strategy games. A notable example is Oil Imperium. It's major feature is, that the gameplay is very slow. The amount of decision to take are working on a high level. The player can relax while the other player takes a move.
This sort of games has felt out of fashion but they are important from the perspective of Artificial Intelligence. Even modern real time strategy games have a high level component which needs only a small amount of decisions. For example the question, if the user likes to build 10 houses or 30 housing. Most games can be split into a low level layer and a high level layer.