In this work, we propose to analyze the evolving dynamics of different collaboration network strategies that emerge from the creation and diffusion of knowledge. In addition, we aim at describing their most relevant network properties over time. We adopt an evolutionary economic approach by avoiding the profit-maximization behavior of firms and introducing decisions rules that are applied routinely. Additionally, the mechanisms of search and selection are considered in order to explain the survival of firms. We developed a Multi-Agent Model with cognitive attributes, where firms (the agents) can collaborate and create networks for R&D purposes. There are three markets (X, Y₁ and Y₂): X is the final good market and Y₁ and Y₂ are the intermediate good markets. In each instant t, there is a stock of knowledge, k^t_i, for every firm i in each market. Links between the firms allow for the diffusion of the knowledge among the firms in the network. For every firm i, at instant t, the accumulation of knowledge k is given by: k^t_i = k^t-1_i + Δk^t_i where Δk^t_i represents the increase on the stock of knowledge of firm i, given its R&D effort but also the R&D effort produced by firms within the network. This effort is pooled by the geographical and technological distance between every pairs of firms and by a transferability factor δ (or spillover), that measures the share of new knowledge which is effectively transmitted through the network. Different collaboration strategies have been designed, involving two different stages: (i) the selection of the partner, and (ii) the process of network formation and growth. After having identified different alternatives for (i) and (ii), as observed in the literature, we have combined them in four strategies: (A) Peer-to-peer Complementariness; (B): Concentration Process; (C) Collaboration networks and (D) Cooperation networks. To measure the impact of the different strategies in the network formation, we have used network indicators as transitivity, average path length and diameter. The strategies were compared and we found out that higher profits are associated with a higher stock of knowledge and a small network diameter. It actually confirms what is said in literature about economic networks, i.e., that the average distance between nodes decreases over time in more profitable networks. In addition, strategy B, in which firms select the most successful partner (the concentration process), is proved to produce more profitable networks. Furthermore, we observed that lower marginal costs are determinant for the growth of networks.

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