What is Artificial Intelligence?

 In contrast to a famous myth, there is an answer available to this question because researchers have investigated the subject for decades. The most famous and easy to understand definition aka introduction towards the subject is a computer chess player. The computer is able to decide for the next move on the board and a modern chess program can beat even a grandmaster.

Computer chess explains at the same time, what current Artificial Intelligence can't provide yet. There is a difference available between a program like gnuchess and a robot. Gnuchess is only able to play chess, while a robot has to do more complex tasks. AI research since the 1980s was devoted towards the goal to improve the skills of a computer.

A promising approach is a reward function based on grounded language. In contrast to a fixed reward function which is used in computer chess, a parametric reward function based on natural language can be modified on the fly. This allows a computer to understand instrauctions like "move to the blue box and grasp it". This command is translated into a reward signal and the computer can plan a trajectory to maximize the reward.

Let us compare computer chess with instruction following in robotics. Computer chess is based on a single fixed evaluation function which converts the current board into a reward signal e.g. 0.4. This numerical information is used by the alpha beta prunning algorithm to find the optimal action. The planner is traversing the game tree upt to 10 steps into the future and decides for an action which maximaizes the reward. This is equal to win the game.

In contrast, instruction following in robotics is offloading the reward signal to a speaker located outisde of the robot. The speaker, determines by its command what the current subgoal is in the game. A possible command might be:

1. "if the battery is empty search for the charging station"
2. "grasp the red box"
3. "bring the red box into room C".

In contrast to the game of chess which has a single goal which remains the same, a warehouse robot can have multiple goals which are acivated in a sequence. The AI makes sure, that the robot understands a goal, in a mathematical sense. Understanding means, that the robot determines the numerical reward for a textual command. For example, if the goal is "grasp the red box" the robot will receive a reward if the gripper moves towards the box and another reward for closing the gipper around the box.

The problem for the programmers and AI engineers is to encode the reward function including the natural language parser in software. A robot who understands a dozens of commands comes close to the goal of building an intelligence machine.

The purpose of a command based reward function is to transform a closed system into an open system. Open means, that the robot is communicating with its environment. The need for doing so is because the robot itself has insufficient knowledge about the task, on the other hand the human operator has much more knowledge. It makes sense to offload the planning task towards the human operator.

In chess playing AI systems from the past with a fixed evaluation function it was not possible to interact with the system during runtime. The only strategy to modify the reward was to stop the program, modify the source the source code and restart the software.