To my knowledge, most chess programs written to date are focused on taking advantage of the computer's calculating powers (aka brute force method). My program will be different in that the focus is going to be on emulating human thinking (in this case my own way of thinking which is actually highly organized).

There are quite a lot of possible chess games (10^120 - the universe has only around 10^80 atoms) so it is quite unpractical to try all solutions (this is what backtracking means).

Instead, most of the solutions actually mimic human thinking. A quite common algorithm is known as Minimax. I am just a casual chess player, but for many games, it seems like humans consider multiple possible moves and try to forecast in their minds what would be the reaction of the opponent on such move (basically continuing the game for a few moves in their head). Minimax does the same thing: analyses the possible moves, picks one such that the best move of the opponent creates the smallest advantage for him. The only difference is that while humans are quite limited in the number of moves they can consider (arguably, they are more clever in picking which ones to consider), the computers can analyse almost every move and consider what the adversary can do.

For chess, this is still quite complicated and there are ways (such as alpha beta pruning) to skip some moves.

Deep blue beat Kasparov, considered at the time to be the best chess player. There are plenty of resources over the web on how it works, but a Minimax algorithm is at the core, along with a lot of clever optimizations and leverage of computational power.

As for which paradigm to choose, this is more a choice of how to get to the destination rather than picking the actual destination. Algorithms are (usually) paradigm agnostic. Different paradigms exist because programmers can leverage them in order to be able to develop and maintain easier the software. All paradigms have, by the Church-Turing thesis, the same computational capabilities.

To my knowledge, most chess programs written to date are focused on taking advantage of the computer's calculating powers (aka brute force method). My program will be different in that the focus is going to be on emulating human thinking (in this case my own way of thinking which is actually highly organized).

There are quite a lot of possible chess games (10^120 - the universe has only around 10^80 atoms) so it is quite unpractical to try all solutions (this is what backtracking means).

Instead, most of the solutions are inspired human thinking. A quite common algorithm is known as Minimax. I am just a casual chess player, but for many games, it seems like humans consider multiple possible moves and try to forecast in their minds what would be the reaction of the opponent on such move (basically continuing the game for a few moves in their head). Minimax does the same thing: analyses the possible moves, picks one such that the best move of the opponent creates the smallest advantage for him. The only difference is that while humans are quite limited in the number of moves they can consider (arguably, they are more clever in picking which ones to consider), the computers can analyse almost every move and consider what the adversary can do.

For chess, this is still quite complicated and there are ways (such as alpha beta pruning) to skip some moves.

Deep blue beat Kasparov, considered at the time to be the best chess player. There are plenty of resources over the web on how it works, but a Minimax algorithm is at the core, along with a lot of clever optimizations and leverage of computational power.

As for which paradigm to choose, this is more a choice of how to get to the destination rather than picking the actual destination. Algorithms are (usually) paradigm agnostic. Different paradigms exist because programmers can leverage them in order to be able to develop and maintain easier the software. All paradigms have, by the Church-Turing thesis, the same computational capabilities.