Solving Pictorial Jigsaw Puzzle by Stigmergy-inspired Internet-based
  Human Collective Intelligence
  The pictorial jigsaw (PJ) puzzle is a well-known leisure game for humans.
Usually, a PJ puzzle game is played by one or several human players
face-to-face in the physical space. In this paper, we focus on how to solve PJ
puzzles in the cyberspace by a group of physically distributed human players.
We propose an approach to solving PJ puzzle by stigmergy-inspired
Internet-based human collective intelligence. The core of the approach is a
continuously executing loop, named the EIF loop, which consists of three
activities: exploration, integration, and feedback. In exploration, each player
tries to solve the PJ puzzle alone, without direct interactions with other
players. At any time, the result of a player's exploration is a partial
solution to the PJ puzzle, and a set of rejected neighboring relation between
pieces. The results of all players' exploration are integrated in real time
through integration, with the output of a continuously updated collective
opinion graph (COG). And through feedback, each player is provided with
personalized feedback information based on the current COG and the player's
exploration result, in order to accelerate his/her puzzle-solving process.
Exploratory experiments show that: (1) supported by this approach, the time to
solve PJ puzzle is nearly linear to the reciprocal of the number of players,
and shows better scalability to puzzle size than that of face-to-face
collaboration for 10-player groups; (2) for groups with 2 to 10 players, the
puzzle-solving time decreases 31.36%-64.57% on average, compared with the best
single players in the experiments.
