
  aaddddNNeett -- ccrreeaatteess aa nneeww nneettwwoorrkk aanndd mmaakkeess iitt tthhee aaccttiivvee nneettwwoorrkk

  UUSSAAGGEE

        addNet <network> [-intervals <timeIntervals> |
            -ticks <ticksPerInterval>] [<net-type>]*
            [<num-units> [[+|-]<group-type>]*]*

  DDEESSCCRRIIPPTTIIOONN

  addNet creates a network with the specified name and makes it the active
  network. Multiple networks may be loaded at the same time but only one may
  be active and most commands will only operate on the active network. _u_s_e_N_e_t
  can be used to list all networks or change the active network.

  If another network with the same name exists, the user will have the option
  of replacing the other network or aborting. The network is created with a
  bias layer, called "bias", which contains a single unit.

  timeIntervals is an integer specifying the maximum "real" time for which
  each example will be run. For non-continuous networks, this is the same as
  the number of events or ticks. For continuous networks, these are in
  abstract time units. The default is 1.

  ticksPerInterval is specific to continuous networks and sets the number of
  ticks or activation updates per time interval. dt will default to the
  inverse of this value.

  Networks default to standard type. Currently, the valid additional types
  are SRBPTT (simple recurrent backprop-through-time), CONTINUOUS (fully
  recurrent), and BOLTZMANN. To get recurrent backprop-through-time (which
  isn't really continuous), leave the ticksPerInterval 1 and use the
  CONTINUOUS type.

  addNet can also be used like the old autoNet to create and connect groups
  in the network with a single command. If group information is listed after
  the network type, they will automatically be added to the network.

  Each group is created by specifying the number of units in the group
  followed by a series of types. Groups will be given names automatically,
  although these could be altered later using:

        lens> setObject group(<i>).name <new-name>

  The group types should be specified exactly as they would be when using
  _a_d_d_G_r_o_u_p or _g_r_o_u_p_T_y_p_e, with the following differences:

  If a fixed type is not specified for the first group, it will default to an
  INPUT group. Likewise, the last group will default to OUTPUT. All other
  groups will default to no fixed type (hidden), although they could be set
  to other fixed types by specifying a type.

  In order to create an Elman context layer, it is not necessary to define it
  as a separate group. Giving any group the type ELMAN will cause a context
  group, having the same number of units, to be created as well. The original
  group will be Elman-connected (a special one-to-one identity mapping) to
  the context group and the context group will have a full projection back to
  the original.

  The first input group will be named "input", with subsequent input groups
  labeled "input2", "input3", etc. Likewise for output and hidden layers. A
  context group will be given the same number as the corresponding main
  group. The context of the first hidden layer would be called "context".
  That of the first output layer would be called "outContext".

  EEXXAAMMPPLLEESS

  To create a new standard network with the name "My Network":

        lens> addNet "My Network"

  To create a new continuous network with 3 time intervals and 5 ticks per
  interval:

        lens> addNet myNet -i 3 -t 5 CONTINUOUS

  The command below creates a simple recurrent network named "myNet" with a
  maximum of 5 time intervals (each with one tick) per example, 10 inputs, 20
  hidden units, 20 context units, and 3 output units. The input layer
  projects to the hidden layer. The hidden layer has an Elman-projection to
  the context layer which has a full projection back to the hidden layer. The
  hidden layer then projects to the output layer. The bias group projects to
  the hidden and output layers, but not the input and context. The output
  group is of type SOFT_MAX.

        lens> addNet myNet -i 5 10 20 ELMAN 3 SOFT_MAX

  SSEEEE AALLSSOO

  _a_d_d_G_r_o_u_p, _c_o_n_n_e_c_t_G_r_o_u_p_s, _e_l_m_a_n_C_o_n_n_e_c_t

  ---------------------------------------------------------------------------
    Last modified: Sat Aug 28.39:29:41 EDT 1999

